Focusing on the golden ball metaheuristic: an extended study on a wider set of problems.

PubMed

Osaba, E; Diaz, F; Carballedo, R; Onieva, E; Perallos, A

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results.

Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems

PubMed Central

Osaba, E.; Diaz, F.; Carballedo, R.; Onieva, E.; Perallos, A.

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results. PMID:25165742

Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm.

PubMed

Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar

2018-01-01

Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Branch-pipe-routing approach for ships using improved genetic algorithm

NASA Astrophysics Data System (ADS)

Sui, Haiteng; Niu, Wentie

2016-09-01

Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into threedimensional (3D) grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.

Multi-terminal pipe routing by Steiner minimal tree and particle swarm optimisation

NASA Astrophysics Data System (ADS)

Liu, Qiang; Wang, Chengen

2012-08-01

Computer-aided design of pipe routing is of fundamental importance for complex equipments' developments. In this article, non-rectilinear branch pipe routing with multiple terminals that can be formulated as a Euclidean Steiner Minimal Tree with Obstacles (ESMTO) problem is studied in the context of an aeroengine-integrated design engineering. Unlike the traditional methods that connect pipe terminals sequentially, this article presents a new branch pipe routing algorithm based on the Steiner tree theory. The article begins with a new algorithm for solving the ESMTO problem by using particle swarm optimisation (PSO), and then extends the method to the surface cases by using geodesics to meet the requirements of routing non-rectilinear pipes on the surfaces of aeroengines. Subsequently, the adaptive region strategy and the basic visibility graph method are adopted to increase the computation efficiency. Numeral computations show that the proposed routing algorithm can find satisfactory routing layouts while running in polynomial time.

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

Optical slotted circuit switched network: a bandwidth efficient alternative to wavelength-routed network

NASA Astrophysics Data System (ADS)

Li, Yan; Collier, Martin

2007-11-01

Wavelength-routed networks have received enormous attention due to the fact that they are relatively simple to implement and implicitly offer Quality of Service (QoS) guarantees. However, they suffer from a bandwidth inefficiency problem and require complex Routing and Wavelength Assignment (RWA). Most attempts to address the above issues exploit the joint use of WDM and TDM technologies. The resultant TDM-based wavelength-routed networks partition the wavelength bandwidth into fixed-length time slots organized as a fixed-length frame. Multiple connections can thus time-share a wavelength and the grooming of their traffic leads to better bandwidth utilization. The capability of switching in both wavelength and time domains in such networks also mitigates the RWA problem. However, TMD-based wavelength-routed networks work in synchronous mode and strict synchronization among all network nodes is required. Global synchronization for all-optical networks which operate at extremely high speed is technically challenging, and deploying an optical synchronizer for each wavelength involves considerable cost. An Optical Slotted Circuit Switching (OSCS) architecture is proposed in this paper. In an OSCS network, slotted circuits are created to better utilize the wavelength bandwidth than in classic wavelength-routed networks. The operation of the protocol is such as to avoid the need for global synchronization required by TDM-based wavelength-routed networks.

An improved least cost routing approach for WDM optical network without wavelength converters

NASA Astrophysics Data System (ADS)

Bonani, Luiz H.; Forghani-elahabad, Majid

2016-12-01

Routing and wavelength assignment (RWA) problem has been an attractive problem in optical networks, and consequently several algorithms have been proposed in the literature to solve this problem. The most known techniques for the dynamic routing subproblem are fixed routing, fixed-alternate routing, and adaptive routing methods. The first one leads to a high blocking probability (BP) and the last one includes a high computational complexity and requires immense backing from the control and management protocols. The second one suggests a trade-off between performance and complexity, and hence we consider it to improve in our work. In fact, considering the RWA problem in a wavelength routed optical network with no wavelength converter, an improved technique is proposed for the routing subproblem in order to decrease the BP of the network. Based on fixed-alternate approach, the first k shortest paths (SPs) between each node pair is determined. We then rearrange the SPs according to a newly defined cost for the links and paths. Upon arriving a connection request, the sorted paths are consecutively checked for an available wavelength according to the most-used technique. We implement our proposed algorithm and the least-hop fixed-alternate algorithm to show how the rearrangement of SPs contributes to a lower BP in the network. The numerical results demonstrate the efficiency of our proposed algorithm in comparison with the others, considering different number of available wavelengths.

Improving delivery routes using combined heuristic and optimization in a consumer goods distribution company

NASA Astrophysics Data System (ADS)

Wibisono, E.; Santoso, A.; Sunaryo, M. A.

2017-11-01

XYZ is a distributor of various consumer goods products. The company plans its delivery routes daily and in order to obtain route construction in a short amount of time, it simplifies the process by assigning drivers based on geographic regions. This approach results in inefficient use of vehicles leading to imbalance workloads. In this paper, we propose a combined method involving heuristic and optimization to obtain better solutions in acceptable computation time. The heuristic is based on a time-oriented, nearest neighbor (TONN) to form clusters if the number of locations is higher than a certain value. The optimization part uses a mathematical modeling formulation based on vehicle routing problem that considers heterogeneous vehicles, time windows, and fixed costs (HVRPTWF) and is used to solve routing problem in clusters. A case study using data from one month of the company’s operations is analyzed, and data from one day of operations are detailed in this paper. The analysis shows that the proposed method results in 24% cost savings on that month, but it can be as high as 54% in a day.

Route Prediction on Tracking Data to Location-Based Services

NASA Astrophysics Data System (ADS)

Petróczi, Attila István; Gáspár-Papanek, Csaba

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

PubMed

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Polynomial Size Formulations for the Distance and Capacity Constrained Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Kara, Imdat; Derya, Tusan

2011-09-01

The Distance and Capacity Constrained Vehicle Routing Problem (DCVRP) is an extension of the well known Traveling Salesman Problem (TSP). DCVRP arises in distribution and logistics problems. It would be beneficial to construct new formulations, which is the main motivation and contribution of this paper. We focused on two indexed integer programming formulations for DCVRP. One node based and one arc (flow) based formulation for DCVRP are presented. Both formulations have O(n2) binary variables and O(n2) constraints, i.e., the number of the decision variables and constraints grows with a polynomial function of the nodes of the underlying graph. It is shown that proposed arc based formulation produces better lower bound than the existing one (this refers to the Water's formulation in the paper). Finally, various problems from literature are solved with the node based and arc based formulations by using CPLEX 8.0. Preliminary computational analysis shows that, arc based formulation outperforms the node based formulation in terms of linear programming relaxation.

A set-covering based heuristic algorithm for the periodic vehicle routing problem.

PubMed

Cacchiani, V; Hemmelmayr, V C; Tricoire, F

2014-01-30

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011)  [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems.

A set-covering based heuristic algorithm for the periodic vehicle routing problem

PubMed Central

Cacchiani, V.; Hemmelmayr, V.C.; Tricoire, F.

2014-01-01

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011)  [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems. PMID:24748696

A novel heuristic algorithm for capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

ZERO: probabilistic routing for deploy and forget Wireless Sensor Networks.

PubMed

Vilajosana, Xavier; Llosa, Jordi; Pacho, Jose Carlos; Vilajosana, Ignasi; Juan, Angel A; Vicario, Jose Lopez; Morell, Antoni

2010-01-01

As Wireless Sensor Networks are being adopted by industry and agriculture for large-scale and unattended deployments, the need for reliable and energy-conservative protocols become critical. Physical and Link layer efforts for energy conservation are not mostly considered by routing protocols that put their efforts on maintaining reliability and throughput. Gradient-based routing protocols route data through most reliable links aiming to ensure 99% packet delivery. However, they suffer from the so-called "hot spot" problem. Most reliable routes waste their energy fast, thus partitioning the network and reducing the area monitored. To cope with this "hot spot" problem we propose ZERO a combined approach at Network and Link layers to increase network lifespan while conserving reliability levels by means of probabilistic load balancing techniques.

Developing teaching process for enhancing students' mathematical problem solving in the 21st century through STEM education

NASA Astrophysics Data System (ADS)

Prawvichien, Sutthaporn; Siripun, Kulpatsorn; Yuenyong, Chokchai

2018-01-01

The STEM education could provide the context for students' learning in the 21st century. The Mathematical problem solving requires a context which simulates real life in order to give students experience of the power of mathematics in the world around them. This study aimed to develop the teaching process for enhancing students' mathematical problem solving in the 21st century through STEM education. The paper will clarify the STEM learning activities about graph theories regarding on the 6 steps of engineering design process. These include identify a challenge, exploring ideas, designing and planning, doing and developing, test and evaluate, and present the solution. The learning activities will start from the Identify a challenge stage which provides the northern part of Thailand flooding situation in order to set the students' tasks of develop the solutions of providing the routes of fastest moving people away from the flooding areas. The explore ideas stage will provide activities for enhance students to learn some knowledge based for designing the possible solutions. This knowledge based could focus on measuring, geometry, graph theory, and mathematical process. The design and plan stage will ask students to model the city based on the map and then provide the possible routes. The doing and development stage will ask students to develop the routes based on their possible model. The test and evaluating will ask students to clarify how to test and evaluate the possible routes, and then test it. The present solution stage will ask students to present the whole process of designing routes. Then, the paper will discuss how these learning activities could enhance students' mathematical problem solving. The paper may have implication for STEM education in school setting.

Analog Processor To Solve Optimization Problems

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.

1993-01-01

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

A model for distribution centers location-routing problem on a multimodal transportation network with a meta-heuristic solving approach

NASA Astrophysics Data System (ADS)

Fazayeli, Saeed; Eydi, Alireza; Kamalabadi, Isa Nakhai

2017-07-01

Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.

A model for distribution centers location-routing problem on a multimodal transportation network with a meta-heuristic solving approach

NASA Astrophysics Data System (ADS)

Fazayeli, Saeed; Eydi, Alireza; Kamalabadi, Isa Nakhai

2018-07-01

Nowadays, organizations have to compete with different competitors in regional, national and international levels, so they have to improve their competition capabilities to survive against competitors. Undertaking activities on a global scale requires a proper distribution system which could take advantages of different transportation modes. Accordingly, the present paper addresses a location-routing problem on multimodal transportation network. The introduced problem follows four objectives simultaneously which form main contribution of the paper; determining multimodal routes between supplier and distribution centers, locating mode changing facilities, locating distribution centers, and determining product delivery tours from the distribution centers to retailers. An integer linear programming is presented for the problem, and a genetic algorithm with a new chromosome structure proposed to solve the problem. Proposed chromosome structure consists of two different parts for multimodal transportation and location-routing parts of the model. Based on published data in the literature, two numerical cases with different sizes generated and solved. Also, different cost scenarios designed to better analyze model and algorithm performance. Results show that algorithm can effectively solve large-size problems within a reasonable time which GAMS software failed to reach an optimal solution even within much longer times.

Nonlinear relative-proportion-based route adjustment process for day-to-day traffic dynamics: modeling, equilibrium and stability analysis

NASA Astrophysics Data System (ADS)

Zhu, Wenlong; Ma, Shoufeng; Tian, Junfang; Li, Geng

2016-11-01

Travelers' route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers' route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model.

Bi-Objective Modelling for Hazardous Materials Road–Rail Multimodal Routing Problem with Railway Schedule-Based Space–Time Constraints

PubMed Central

Sun, Yan; Lang, Maoxiang; Wang, Danzhu

2016-01-01

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294

Routing Algorithm based on Minimum Spanning Tree and Minimum Cost Flow for Hybrid Wireless-optical Broadband Access Network

NASA Astrophysics Data System (ADS)

Le, Zichun; Suo, Kaihua; Fu, Minglei; Jiang, Ling; Dong, Wen

2012-03-01

In order to minimize the average end to end delay for data transporting in hybrid wireless optical broadband access network, a novel routing algorithm named MSTMCF (minimum spanning tree and minimum cost flow) is devised. The routing problem is described as a minimum spanning tree and minimum cost flow model and corresponding algorithm procedures are given. To verify the effectiveness of MSTMCF algorithm, extensively simulations based on OWNS have been done under different types of traffic source.

Problems With Deployment of Multi-Domained, Multi-Homed Mobile Networks

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2008-01-01

This document describes numerous problems associated with deployment of multi-homed mobile platforms consisting of multiple networks and traversing large geographical areas. The purpose of this document is to provide insight to real-world deployment issues and provide information to groups that are addressing many issues related to multi-homing, policy-base routing, route optimization and mobile security - particularly those groups within the Internet Engineering Task Force.

A Formal Algorithm for Routing Traces on a Printed Circuit Board

NASA Technical Reports Server (NTRS)

Hedgley, David R., Jr.

1996-01-01

This paper addresses the classical problem of printed circuit board routing: that is, the problem of automatic routing by a computer other than by brute force that causes the execution time to grow exponentially as a function of the complexity. Most of the present solutions are either inexpensive but not efficient and fast, or efficient and fast but very costly. Many solutions are proprietary, so not much is written or known about the actual algorithms upon which these solutions are based. This paper presents a formal algorithm for routing traces on a print- ed circuit board. The solution presented is very fast and efficient and for the first time speaks to the question eloquently by way of symbolic statements.

Formal Approach For Resilient Reachability based on End-System Route Agility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rauf, Usman; Gillani, Fida; Al-Shaer, Ehab

The deterministic nature of existing routing protocols has resulted into an ossified Internet with static and predictable network routes. This gives persistent attackers (e.g. eavesdroppers and DDoS attackers) plenty of time to study the network and identify the vulnerable links (critical) to plan a devastating and stealthy attack. Recently, route mutation approaches have been proposed to address such issues. However, these approaches incur significantly high overhead and depend upon the availability of disjoint routes in the network, which inherently limit their use for mission critical services. To cope with these issues, we extend the current routing architecture to consider end-hostsmore » as routing elements, and present a formal method based agile defense mechanism to increase resiliency of the existing cyber infrastructure. The major contributions of this paper include: (1) formalization of efficient and resilient End to End (E2E) reachability problem as a constraint satisfaction problem, which identifies the potential end-hosts to reach a destination while satisfying resilience and QoS constraints, (2) design and implementation of a novel decentralized End Point Route Mutation (EPRM) protocol, and (3) design and implementation of planning algorithm to minimize the overlap between multiple flows, for the sake of maximizing the agility in the system. Our implementation and evaluation validates the correctness, effectiveness and scalability of the proposed approach.« less

Optimal route discovery for soft QOS provisioning in mobile ad hoc multimedia networks

NASA Astrophysics Data System (ADS)

Huang, Lei; Pan, Feng

2007-09-01

In this paper, we propose an optimal routing discovery algorithm for ad hoc multimedia networks whose resource keeps changing, First, we use stochastic models to measure the network resource availability, based on the information about the location and moving pattern of the nodes, as well as the link conditions between neighboring nodes. Then, for a certain multimedia packet flow to be transmitted from a source to a destination, we formulate the optimal soft-QoS provisioning problem as to find the best route that maximize the probability of satisfying its desired QoS requirements in terms of the maximum delay constraints. Based on the stochastic network resource model, we developed three approaches to solve the formulated problem: A centralized approach serving as the theoretical reference, a distributed approach that is more suitable to practical real-time deployment, and a distributed dynamic approach that utilizes the updated time information to optimize the routing for each individual packet. Examples of numerical results demonstrated that using the route discovered by our distributed algorithm in a changing network environment, multimedia applications could achieve better QoS statistically.

Joint optimization of green vehicle scheduling and routing problem with time-varying speeds

PubMed Central

Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo

2018-01-01

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370

Joint optimization of green vehicle scheduling and routing problem with time-varying speeds.

PubMed

Zhang, Dezhi; Wang, Xin; Li, Shuangyan; Ni, Nan; Zhang, Zhuo

2018-01-01

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions.

Practice makes proficient: pigeons (Columba livia) learn efficient routes on full-circuit navigational traveling salesperson problems.

PubMed

Baron, Danielle M; Ramirez, Alejandro J; Bulitko, Vadim; Madan, Christopher R; Greiner, Ariel; Hurd, Peter L; Spetch, Marcia L

2015-01-01

Visiting multiple locations and returning to the start via the shortest route, referred to as the traveling salesman (or salesperson) problem (TSP), is a valuable skill for both humans and non-humans. In the current study, pigeons were trained with increasing set sizes of up to six goals, with each set size presented in three distinct configurations, until consistency in route selection emerged. After training at each set size, the pigeons were tested with two novel configurations. All pigeons acquired routes that were significantly more efficient (i.e., shorter in length) than expected by chance selection of the goals. On average, the pigeons also selected routes that were more efficient than expected based on a local nearest-neighbor strategy and were as efficient as the average route generated by a crossing-avoidance strategy. Analysis of the routes taken indicated that they conformed to both a nearest-neighbor and a crossing-avoidance strategy significantly more often than expected by chance. Both the time taken to visit all goals and the actual distance traveled decreased from the first to the last trials of training in each set size. On the first trial with novel configurations, average efficiency was higher than chance, but was not higher than expected from a nearest-neighbor or crossing-avoidance strategy. These results indicate that pigeons can learn to select efficient routes on a TSP problem.

The Route Analysis Based On Flight Plan

NASA Astrophysics Data System (ADS)

Feriyanto, Nur; Saleh, Chairul; Fauzi, Achmad; Rachman Dzakiyullah, Nur; Riza Iwaputra, Kahfi

2016-02-01

Economic development effects use of air transportation since the business process in every aspect was increased. Many people these days was prefer using airplane because it can save time and money. This situation also effects flight routes, many airlines offer new routes to deal with competition. Managing flight routes is one of the problems that must be faced in order to find the efficient and effective routes. This paper investigates the best routes based on flight performance by determining the amount of block fuel for the Jakarta-Denpasar flight route. Moreover, in this work compares a two kinds of aircraft and tracks by calculating flight distance, flight time and block fuel. The result shows Jakarta-Denpasar in the Track II has effective and efficient block fuel that can be performed by Airbus 320-200 aircraft. This study can contribute to practice in making an effective decision, especially helping executive management of company due to selecting appropriate aircraft and the track in the flight plan based on the block fuel consumption for business operation.

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Benchmark dataset for undirected and Mixed Capacitated Arc Routing Problems under Time restrictions with Intermediate Facilities.

PubMed

Willemse, Elias J; Joubert, Johan W

2016-09-01

In this article we present benchmark datasets for the Mixed Capacitated Arc Routing Problem under Time restrictions with Intermediate Facilities (MCARPTIF). The problem is a generalisation of the Capacitated Arc Routing Problem (CARP), and closely represents waste collection routing. Four different test sets are presented, each consisting of multiple instance files, and which can be used to benchmark different solution approaches for the MCARPTIF. An in-depth description of the datasets can be found in "Constructive heuristics for the Mixed Capacity Arc Routing Problem under Time Restrictions with Intermediate Facilities" (Willemseand Joubert, 2016) [2] and "Splitting procedures for the Mixed Capacitated Arc Routing Problem under Time restrictions with Intermediate Facilities" (Willemseand Joubert, in press) [4]. The datasets are publicly available from "Library of benchmark test sets for variants of the Capacitated Arc Routing Problem under Time restrictions with Intermediate Facilities" (Willemse and Joubert, 2016) [3].

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Self-adaptive trust based ABR protocol for MANETs using Q-learning.

PubMed

Kumar, Anitha Vijaya; Jeyapal, Akilandeswari

2014-01-01

Mobile ad hoc networks (MANETs) are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR) protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation.

Self-Adaptive Trust Based ABR Protocol for MANETs Using Q-Learning

PubMed Central

Jeyapal, Akilandeswari

2014-01-01

Mobile ad hoc networks (MANETs) are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR) protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation. PMID:25254243

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

Lead Exposure Hazard Management Guide

DTIC Science & Technology

1993-12-01

that may pose chemical or physical problems . Make this section specific to your base or location. b. Exposure Routes. The potential routes of...Pregnant Mother ........ 14 nstallatio (Base) Lead Te xicity Investigations . Team Makeup and Duties ............ 15 Lead Toxicity Investigation...occurring in tradesmen who used lead in their occupations. The favorable physical and chemical properties of lead accounted for its extensive use. Lead can

Zone-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads. PMID:27437455

Zone-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads.

Forwarding techniques for IP fragmented packets in a real 6LoWPAN network.

PubMed

Ludovici, Alessandro; Calveras, Anna; Casademont, Jordi

2011-01-01

Wireless Sensor Networks (WSNs) are attracting more and more interest since they offer a low-cost solution to the problem of providing a means to deploy large sensor networks in a number of application domains. We believe that a crucial aspect to facilitate WSN diffusion is to make them interoperable with external IP networks. This can be achieved by using the 6LoWPAN protocol stack. 6LoWPAN enables the transmission of IPv6 packets over WSNs based on the IEEE 802.15.4 standard. IPv6 packet size is considerably larger than that of IEEE 802.15.4 data frame. To overcome this problem, 6LoWPAN introduces an adaptation layer between the network and data link layers, allowing IPv6 packets to be adapted to the lower layer constraints. This adaptation layer provides fragmentation and header compression of IP packets. Furthermore, it also can be involved in routing decisions. Depending on which layer is responsible for routing decisions, 6LoWPAN divides routing in two categories: mesh under if the layer concerned is the adaptation layer and route over if it is the network layer. In this paper we analyze different routing solutions (route over, mesh under and enhanced route over) focusing on how they forward fragments. We evaluate their performance in terms of latency and energy consumption when transmitting IP fragmented packets. All the tests have been performed in a real 6LoWPAN implementation. After consideration of the main problems in forwarding of mesh frames in WSN, we propose and analyze a new alternative scheme based on mesh under, which we call controlled mesh under.

Forwarding Techniques for IP Fragmented Packets in a Real 6LoWPAN Network

PubMed Central

Ludovici, Alessandro; Calveras, Anna; Casademont, Jordi

2011-01-01

Wireless Sensor Networks (WSNs) are attracting more and more interest since they offer a low-cost solution to the problem of providing a means to deploy large sensor networks in a number of application domains. We believe that a crucial aspect to facilitate WSN diffusion is to make them interoperable with external IP networks. This can be achieved by using the 6LoWPAN protocol stack. 6LoWPAN enables the transmission of IPv6 packets over WSNs based on the IEEE 802.15.4 standard. IPv6 packet size is considerably larger than that of IEEE 802.15.4 data frame. To overcome this problem, 6LoWPAN introduces an adaptation layer between the network and data link layers, allowing IPv6 packets to be adapted to the lower layer constraints. This adaptation layer provides fragmentation and header compression of IP packets. Furthermore, it also can be involved in routing decisions. Depending on which layer is responsible for routing decisions, 6LoWPAN divides routing in two categories: mesh under if the layer concerned is the adaptation layer and route over if it is the network layer. In this paper we analyze different routing solutions (route over, mesh under and enhanced route over) focusing on how they forward fragments. We evaluate their performance in terms of latency and energy consumption when transmitting IP fragmented packets. All the tests have been performed in a real 6LoWPAN implementation. After consideration of the main problems in forwarding of mesh frames in WSN, we propose and analyze a new alternative scheme based on mesh under, which we call controlled mesh under. PMID:22346615

On the improvement of blood sample collection at clinical laboratories

PubMed Central

2014-01-01

Background Blood samples are usually collected daily from different collection points, such hospitals and health centers, and transported to a core laboratory for testing. This paper presents a project to improve the collection routes of two of the largest clinical laboratories in Spain. These routes must be designed in a cost-efficient manner while satisfying two important constraints: (i) two-hour time windows between collection and delivery, and (ii) vehicle capacity. Methods A heuristic method based on a genetic algorithm has been designed to solve the problem of blood sample collection. The user enters the following information for each collection point: postal address, average collecting time, and average demand (in thermal containers). After implementing the algorithm using C programming, this is run and, in few seconds, it obtains optimal (or near-optimal) collection routes that specify the collection sequence for each vehicle. Different scenarios using various types of vehicles have been considered. Unless new collection points are added or problem parameters are changed substantially, routes need to be designed only once. Results The two laboratories in this study previously planned routes manually for 43 and 74 collection points, respectively. These routes were covered by an external carrier company. With the implementation of this algorithm, the number of routes could be reduced from ten to seven in one laboratory and from twelve to nine in the other, which represents significant annual savings in transportation costs. Conclusions The algorithm presented can be easily implemented in other laboratories that face this type of problem, and it is particularly interesting and useful as the number of collection points increases. The method designs blood collection routes with reduced costs that meet the time and capacity constraints of the problem. PMID:24406140

A neural networks-based hybrid routing protocol for wireless mesh networks.

PubMed

Kojić, Nenad; Reljin, Irini; Reljin, Branimir

2012-01-01

The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks

PubMed Central

Kojić, Nenad; Reljin, Irini; Reljin, Branimir

2012-01-01

The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance. PMID:22969360

Vehicle routing problem and capacitated vehicle routing problem frameworks in fund allocation problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2016-11-01

Two new methods adopted from methods commonly used in the field of transportation and logistics are proposed to solve a specific issue of investment allocation problem. Vehicle routing problem and capacitated vehicle routing methods are applied to optimize the fund allocation of a portfolio of investment assets. This is done by determining the sequence of the assets. As a result, total investment risk is minimized by this sequence.

Scheduling of an aircraft fleet

NASA Technical Reports Server (NTRS)

Paltrinieri, Massimo; Momigliano, Alberto; Torquati, Franco

1992-01-01

Scheduling is the task of assigning resources to operations. When the resources are mobile vehicles, they describe routes through the served stations. To emphasize such aspect, this problem is usually referred to as the routing problem. In particular, if vehicles are aircraft and stations are airports, the problem is known as aircraft routing. This paper describes the solution to such a problem developed in OMAR (Operative Management of Aircraft Routing), a system implemented by Bull HN for Alitalia. In our approach, aircraft routing is viewed as a Constraint Satisfaction Problem. The solving strategy combines network consistency and tree search techniques.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

A memetic optimization algorithm for multi-constrained multicast routing in ad hoc networks.

PubMed

Ramadan, Rahab M; Gasser, Safa M; El-Mahallawy, Mohamed S; Hammad, Karim; El Bakly, Ahmed M

2018-01-01

A mobile ad hoc network is a conventional self-configuring network where the routing optimization problem-subject to various Quality-of-Service (QoS) constraints-represents a major challenge. Unlike previously proposed solutions, in this paper, we propose a memetic algorithm (MA) employing an adaptive mutation parameter, to solve the multicast routing problem with higher search ability and computational efficiency. The proposed algorithm utilizes an updated scheme, based on statistical analysis, to estimate the best values for all MA parameters and enhance MA performance. The numerical results show that the proposed MA improved the delay and jitter of the network, while reducing computational complexity as compared to existing algorithms.

Analysis of the single-vehicle cyclic inventory routing problem

NASA Astrophysics Data System (ADS)

Aghezzaf, El-Houssaine; Zhong, Yiqing; Raa, Birger; Mateo, Manel

2012-11-01

The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of a repetitive distribution of a product from a single depot to a selected subset of customers. For each customer, selected for replenishments, the supplier collects a corresponding fixed reward. The objective is to determine the subset of customers to replenish, the quantity of the product to be delivered to each and to design the vehicle route so that the resulting profit (difference between the total reward and the total logistical cost) is maximised while preventing stockouts at each of the selected customers. This problem appears often as a sub-problem in many logistical problems. In this article, the SV-CIRP is formulated as a mixed-integer program with a nonlinear objective function. After a thorough analysis of the structure of the problem and its features, an exact algorithm for its solution is proposed. This exact algorithm requires only solutions of linear mixed-integer programs. Values of a savings-based heuristic for this problem are compared to the optimal values obtained for a set of some test problems. In general, the gap may get as large as 25%, which justifies the effort to continue exploring and developing exact and approximation algorithms for the SV-CIRP.

Determination of optimal self-drive tourism route using the orienteering problem method

NASA Astrophysics Data System (ADS)

Hashim, Zakiah; Ismail, Wan Rosmanira; Ahmad, Norfaieqah

2013-04-01

This paper was conducted to determine the optimal travel routes for self-drive tourism based on the allocation of time and expense by maximizing the amount of attraction scores assigned to each city involved. Self-drive tourism represents a type of tourism where tourists hire or travel by their own vehicle. It only involves a tourist destination which can be linked with a network of roads. Normally, the traveling salesman problem (TSP) and multiple traveling salesman problems (MTSP) method were used in the minimization problem such as determination the shortest time or distance traveled. This paper involved an alternative approach for maximization method which is maximize the attraction scores and tested on tourism data for ten cities in Kedah. A set of priority scores are used to set the attraction score at each city. The classical approach of the orienteering problem was used to determine the optimal travel route. This approach is extended to the team orienteering problem and the two methods were compared. These two models have been solved by using LINGO12.0 software. The results indicate that the model involving the team orienteering problem provides a more appropriate solution compared to the orienteering problem model.

Advances in optimal routing through computer networks

NASA Technical Reports Server (NTRS)

Paz, I. M.

1977-01-01

The optimal routing problem is defined. Progress in solving the problem during the previous decade is reviewed, with special emphasis on technical developments made during the last few years. The relationships between the routing, the throughput, and the switching technology used are discussed and their future trends are reviewed. Economic aspects are also briefly considered. Modern technical approaches for handling the routing problems and, more generally, the flow control problems are reviewed.

Reinforcement learning for resource allocation in LEO satellite networks.

PubMed

Usaha, Wipawee; Barria, Javier A

2007-06-01

In this paper, we develop and assess online decision-making algorithms for call admission and routing for low Earth orbit (LEO) satellite networks. It has been shown in a recent paper that, in a LEO satellite system, a semi-Markov decision process formulation of the call admission and routing problem can achieve better performance in terms of an average revenue function than existing routing methods. However, the conventional dynamic programming (DP) numerical solution becomes prohibited as the problem size increases. In this paper, two solution methods based on reinforcement learning (RL) are proposed in order to circumvent the computational burden of DP. The first method is based on an actor-critic method with temporal-difference (TD) learning. The second method is based on a critic-only method, called optimistic TD learning. The algorithms enhance performance in terms of requirements in storage, computational complexity and computational time, and in terms of an overall long-term average revenue function that penalizes blocked calls. Numerical studies are carried out, and the results obtained show that the RL framework can achieve up to 56% higher average revenue over existing routing methods used in LEO satellite networks with reasonable storage and computational requirements.

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

NASA Astrophysics Data System (ADS)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment

NASA Astrophysics Data System (ADS)

Barnawi, Waleed T.

Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned vehicle. Civil applications that involve missions where human observability would be limited could benefit from the independent UAV task assignment, such as exploration and fire surveillance are also notable uses for this approach.

AVQS: attack route-based vulnerability quantification scheme for smart grid.

PubMed

Ko, Jongbin; Lim, Hyunwoo; Lee, Seokjun; Shon, Taeshik

2014-01-01

A smart grid is a large, consolidated electrical grid system that includes heterogeneous networks and systems. Based on the data, a smart grid system has a potential security threat in its network connectivity. To solve this problem, we develop and apply a novel scheme to measure the vulnerability in a smart grid domain. Vulnerability quantification can be the first step in security analysis because it can help prioritize the security problems. However, existing vulnerability quantification schemes are not suitable for smart grid because they do not consider network vulnerabilities. We propose a novel attack route-based vulnerability quantification scheme using a network vulnerability score and an end-to-end security score, depending on the specific smart grid network environment to calculate the vulnerability score for a particular attack route. To evaluate the proposed approach, we derive several attack scenarios from the advanced metering infrastructure domain. The experimental results of the proposed approach and the existing common vulnerability scoring system clearly show that we need to consider network connectivity for more optimized vulnerability quantification.

Methodology of mixed load customized bus lines and adjustment based on time windows

PubMed Central

Song, Rui

2018-01-01

Custom bus routes need to be optimized to meet the needs of a customized bus for personalized trips of different passengers. This paper introduced a customized bus routing problem in which trips for each depot are given, and each bus stop has a fixed time window within which trips should be completed. Treating a trip as a virtual stop was the first consideration in solving the school bus routing problem (SBRP). Then, the mixed load custom bus routing model was established with a time window that satisfies its requirement and the result were solved by Cplex software. Finally, a simple network diagram with three depots, four pickup stops, and five delivery stops was structured to verify the correctness of the model, and based on the actual example, the result is that all the buses ran 124.42 kilometers, the sum of kilometers was 10.35 kilometers less than before. The paths and departure times of the different busses that were provided by the model were evaluated to meet the needs of the given conditions, thus providing valuable information for actual work. PMID:29320505

Defence against Black Hole and Selective Forwarding Attacks for Medical WSNs in the IoT †

PubMed Central

Mathur, Avijit; Newe, Thomas; Rao, Muzaffar

2016-01-01

Wireless sensor networks (WSNs) are being used to facilitate monitoring of patients in hospital and home environments. These systems consist of a variety of different components/sensors and many processes like clustering, routing, security, and self-organization. Routing is necessary for medical-based WSNs because it allows remote data delivery and it facilitates network scalability in large hospitals. However, routing entails several problems, mainly due to the open nature of wireless networks, and these need to be addressed. This paper looks at two of the problems that arise due to wireless routing between the nodes and access points of a medical WSN (for IoT use): black hole and selective forwarding (SF) attacks. A solution to the former can readily be provided through the use of cryptographic hashes, while the latter makes use of a neighbourhood watch and threshold-based analysis to detect and correct SF attacks. The scheme proposed here is capable of detecting a selective forwarding attack with over 96% accuracy and successfully identifying the malicious node with 83% accuracy. PMID:26797620

IJS: An Intelligent Junction Selection Based Routing Protocol for VANET to Support ITS Services.

PubMed

Bhoi, Sourav Kumar; Khilar, Pabitra Mohan

2014-01-01

Selecting junctions intelligently for data transmission provides better intelligent transportation system (ITS) services. The main problem in vehicular communication is high disturbances of link connectivity due to mobility and less density of vehicles. If link conditions are predicted earlier, then there is a less chance of performance degradation. In this paper, an intelligent junction selection based routing protocol (IJS) is proposed to transmit the data in a quickest path, in which the vehicles are mostly connected and have less link connectivity problem. In this protocol, a helping vehicle is set at every junction to control the communication by predicting link failures or network gaps in a route. Helping vehicle at the junction produces a score for every neighboring junction to forward the data to the destination by considering the current traffic information and selects that junction which has minimum score. IJS protocol is implemented and compared with GyTAR, A-STAR, and GSR routing protocols. Simulation results show that IJS performs better in terms of average end-to-end delay, network gap encounter, and number of hops.

IJS: An Intelligent Junction Selection Based Routing Protocol for VANET to Support ITS Services

PubMed Central

Khilar, Pabitra Mohan

2014-01-01

Selecting junctions intelligently for data transmission provides better intelligent transportation system (ITS) services. The main problem in vehicular communication is high disturbances of link connectivity due to mobility and less density of vehicles. If link conditions are predicted earlier, then there is a less chance of performance degradation. In this paper, an intelligent junction selection based routing protocol (IJS) is proposed to transmit the data in a quickest path, in which the vehicles are mostly connected and have less link connectivity problem. In this protocol, a helping vehicle is set at every junction to control the communication by predicting link failures or network gaps in a route. Helping vehicle at the junction produces a score for every neighboring junction to forward the data to the destination by considering the current traffic information and selects that junction which has minimum score. IJS protocol is implemented and compared with GyTAR, A-STAR, and GSR routing protocols. Simulation results show that IJS performs better in terms of average end-to-end delay, network gap encounter, and number of hops. PMID:27433485

Defence against Black Hole and Selective Forwarding Attacks for Medical WSNs in the IoT.

PubMed

Mathur, Avijit; Newe, Thomas; Rao, Muzaffar

2016-01-19

Wireless sensor networks (WSNs) are being used to facilitate monitoring of patients in hospital and home environments. These systems consist of a variety of different components/sensors and many processes like clustering, routing, security, and self-organization. Routing is necessary for medical-based WSNs because it allows remote data delivery and it facilitates network scalability in large hospitals. However, routing entails several problems, mainly due to the open nature of wireless networks, and these need to be addressed. This paper looks at two of the problems that arise due to wireless routing between the nodes and access points of a medical WSN (for IoT use): black hole and selective forwarding (SF) attacks. A solution to the former can readily be provided through the use of cryptographic hashes, while the latter makes use of a neighbourhood watch and threshold-based analysis to detect and correct SF attacks. The scheme proposed here is capable of detecting a selective forwarding attack with over 96% accuracy and successfully identifying the malicious node with 83% accuracy.

Optimization of location routing inventory problem with transshipment

NASA Astrophysics Data System (ADS)

Ghani, Nor Edayu Abd; Shariff, S. Sarifah Radiah; Zahari, Siti Meriam

2015-05-01

Location Routing Inventory Problem (LRIP) is a collaboration of the three components in the supply chain. It is confined by location-allocation, vehicle routing and inventory management. The aim of the study is to minimize the total system cost in the supply chain. Transshipment is introduced in order to allow the products to be shipped to a customer who experiences a shortage, either directly from the supplier or from another customer. In the study, LRIP is introduced with the transshipment (LRIPT) and customers act as the transshipment points. We select the transshipment point by using the p-center and we present the results in two divisions of cases. Based on the analysis, the results indicated that LRIPT performed well compared to LRIP.

The effect of model uncertainty on some optimal routing problems

NASA Technical Reports Server (NTRS)

Mohanty, Bibhu; Cassandras, Christos G.

1991-01-01

The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

A social activity and physical contact-based routing algorithm in mobile opportunistic networks for emergency response to sudden disasters

NASA Astrophysics Data System (ADS)

Wang, Xiaoming; Lin, Yaguang; Zhang, Shanshan; Cai, Zhipeng

2017-05-01

Sudden disasters such as earthquake, flood and hurricane necessitate the employment of communication networks to carry out emergency response activities. Routing has a significant impact on the functionality, performance and flexibility of communication networks. In this article, the routing problem is studied considering the delivery ratio of messages, the overhead ratio of messages and the average delay of messages in mobile opportunistic networks (MONs) for enterprise-level emergency response communications in sudden disaster scenarios. Unlike the traditional routing methods for MONS, this article presents a new two-stage spreading and forwarding dynamic routing algorithm based on the proposed social activity degree and physical contact factor for mobile customers. A new modelling method for describing a dynamic evolving process of the topology structure of a MON is first proposed. Then a multi-copy spreading strategy based on the social activity degree of nodes and a single-copy forwarding strategy based on the physical contact factor between nodes are designed. Compared with the most relevant routing algorithms such as Epidemic, Prophet, Labelled-sim, Dlife-comm and Distribute-sim, the proposed routing algorithm can significantly increase the delivery ratio of messages, and decrease the overhead ratio and average delay of messages.

Visualizing Internet routing changes.

PubMed

Lad, Mohit; Massey, Dan; Zhang, Lixia

2006-01-01

Today's Internet provides a global data delivery service to millions of end users and routing protocols play a critical role in this service. It is important to be able to identify and diagnose any problems occurring in Internet routing. However, the Internet's sheer size makes this task difficult. One cannot easily extract out the most important or relevant routing information from the large amounts of data collected from multiple routers. To tackle this problem, we have developed Link-Rank, a tool to visualize Internet routing changes at the global scale. Link-Rank weighs links in a topological graph by the number of routes carried over each link and visually captures changes in link weights in the form of a topological graph with adjustable size. Using Link-Rank, network operators can easily observe important routing changes from massive amounts of routing data, discover otherwise unnoticed routing problems, understand the impact of topological events, and infer root causes of observed routing changes.

Population resizing on fitness improvement genetic algorithm to optimize promotion visit route based on android and google maps API

NASA Astrophysics Data System (ADS)

Listyorini, Tri; Muzid, Syafiul

2017-06-01

The promotion team of Muria Kudus University (UMK) has done annual promotion visit to several senior high schools in Indonesia. The visits were done to numbers of schools in Kudus, Jepara, Demak, Rembang and Purwodadi. To simplify the visit, each visit round is limited to 15 (fifteen) schools. However, the team frequently faces some obstacles during the visit, particularly in determining the route that they should take toward the targeted school. It is due to the long distance or the difficult route to reach the targeted school that leads to elongated travel duration and inefficient fuel cost. To solve these problems, the development of a certain application using heuristic genetic algorithm method based on the dynamic of population size or Population Resizing on Fitness lmprovement Genetic Algorithm (PRoFIGA), was done. This android-based application was developed to make the visit easier and to determine a shorter route for the team, hence, the visiting period will be effective and efficient. The result of this research was an android-based application to determine the shortest route by combining heuristic method and Google Maps Application Programming lnterface (API) that display the route options for the team.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

Security-Oriented and Load-Balancing Wireless Data Routing Game in the Integration of Advanced Metering Infrastructure Network in Smart Grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Fulin; Cao, Yang; Zhang, Jun Jason

Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that themore » chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.« less

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

NASA Astrophysics Data System (ADS)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

Multipoint to multipoint routing and wavelength assignment in multi-domain optical networks

NASA Astrophysics Data System (ADS)

Qin, Panke; Wu, Jingru; Li, Xudong; Tang, Yongli

2018-01-01

In multi-point to multi-point (MP2MP) routing and wavelength assignment (RWA) problems, researchers usually assume the optical networks to be a single domain. However, the optical networks develop toward to multi-domain and larger scale in practice. In this context, multi-core shared tree (MST)-based MP2MP RWA are introduced problems including optimal multicast domain sequence selection, core nodes belonging in which domains and so on. In this letter, we focus on MST-based MP2MP RWA problems in multi-domain optical networks, mixed integer linear programming (MILP) formulations to optimally construct MP2MP multicast trees is presented. A heuristic algorithm base on network virtualization and weighted clustering algorithm (NV-WCA) is proposed. Simulation results show that, under different traffic patterns, the proposed algorithm achieves significant improvement on network resources occupation and multicast trees setup latency in contrast with the conventional algorithms which were proposed base on a single domain network environment.

Facilitating the 3D Indoor Search and Rescue Problem: An Overview of the Problem and an Ant Colony Solution Approach

NASA Astrophysics Data System (ADS)

Tashakkori, H.; Rajabifard, A.; Kalantari, M.

2016-10-01

Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.

Prediction based Greedy Perimeter Stateless Routing Protocol for Vehicular Self-organizing Network

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Fan, Quanrun; Chen, Xiaolin; Xu, Wanjin

2018-03-01

PGPSR (Prediction based Greedy Perimeter Stateless Routing) is based on and extended the GPSR protocol to adapt to the high speed mobility of the vehicle auto organization network (VANET) and the changes in the network topology. GPSR is used in the VANET network environment, the network loss rate and throughput are not ideal, even cannot work. Aiming at the problems of the GPSR, the proposed PGPSR routing protocol, it redefines the hello and query packet structure, in the structure of the new node speed and direction information, which received the next update before you can take advantage of its speed and direction to predict the position of node and new network topology, select the right the next hop routing and path. Secondly, the update of the outdated node information of the neighbor’s table is deleted in time. The simulation experiment shows the performance of PGPSR is better than that of GPSR.

Routing Protocols for Underwater Wireless Sensor Networks: Taxonomy, Research Challenges, Routing Strategies and Future Directions.

PubMed

Khan, Anwar; Ali, Ihsan; Ghani, Abdullah; Khan, Nawsher; Alsaqer, Mohammed; Rahman, Atiq Ur; Mahmood, Hasan

2018-05-18

Recent research in underwater wireless sensor networks (UWSNs) has gained the attention of researchers in academia and industry for a number of applications. They include disaster and earthquake prediction, water quality and environment monitoring, leakage and mine detection, military surveillance and underwater navigation. However, the aquatic medium is associated with a number of limitations and challenges: long multipath delay, high interference and noise, harsh environment, low bandwidth and limited battery life of the sensor nodes. These challenges demand research techniques and strategies to be overcome in an efficient and effective fashion. The design of routing protocols for UWSNs is one of the promising solutions to cope with these challenges. This paper presents a survey of the routing protocols for UWSNs. For the ease of description, the addressed routing protocols are classified into two groups: localization-based and localization-free protocols. These groups are further subdivided according to the problems they address or the major parameters they consider during routing. Unlike the existing surveys, this survey considers only the latest and state-of-the-art routing protocols. In addition, every protocol is described in terms of its routing strategy and the problem it addresses and solves. The merit(s) of each protocol is (are) highlighted along with the cost. A description of the protocols in this fashion has a number of advantages for researchers, as compared to the existing surveys. Firstly, the description of the routing strategy of each protocol makes its routing operation easily understandable. Secondly, the demerit(s) of a protocol provides (provide) insight into overcoming its flaw(s) in future investigation. This, in turn, leads to the foundation of new protocols that are more intelligent, robust and efficient with respect to the desired parameters. Thirdly, a protocol can be selected for the appropriate application based on its described merit(s). Finally, open challenges and research directions are presented for future investigation.

Routing Protocols for Underwater Wireless Sensor Networks: Taxonomy, Research Challenges, Routing Strategies and Future Directions

PubMed Central

Ghani, Abdullah; Alsaqer, Mohammed; Rahman, Atiq Ur; Mahmood, Hasan

2018-01-01

Recent research in underwater wireless sensor networks (UWSNs) has gained the attention of researchers in academia and industry for a number of applications. They include disaster and earthquake prediction, water quality and environment monitoring, leakage and mine detection, military surveillance and underwater navigation. However, the aquatic medium is associated with a number of limitations and challenges: long multipath delay, high interference and noise, harsh environment, low bandwidth and limited battery life of the sensor nodes. These challenges demand research techniques and strategies to be overcome in an efficient and effective fashion. The design of routing protocols for UWSNs is one of the promising solutions to cope with these challenges. This paper presents a survey of the routing protocols for UWSNs. For the ease of description, the addressed routing protocols are classified into two groups: localization-based and localization-free protocols. These groups are further subdivided according to the problems they address or the major parameters they consider during routing. Unlike the existing surveys, this survey considers only the latest and state-of-the-art routing protocols. In addition, every protocol is described in terms of its routing strategy and the problem it addresses and solves. The merit(s) of each protocol is (are) highlighted along with the cost. A description of the protocols in this fashion has a number of advantages for researchers, as compared to the existing surveys. Firstly, the description of the routing strategy of each protocol makes its routing operation easily understandable. Secondly, the demerit(s) of a protocol provides (provide) insight into overcoming its flaw(s) in future investigation. This, in turn, leads to the foundation of new protocols that are more intelligent, robust and efficient with respect to the desired parameters. Thirdly, a protocol can be selected for the appropriate application based on its described merit(s). Finally, open challenges and research directions are presented for future investigation. PMID:29783686

About some types of constraints in problems of routing

NASA Astrophysics Data System (ADS)

Petunin, A. A.; Polishuk, E. G.; Chentsov, A. G.; Chentsov, P. A.; Ukolov, S. S.

2016-12-01

Many routing problems arising in different applications can be interpreted as a discrete optimization problem with additional constraints. The latter include generalized travelling salesman problem (GTSP), to which task of tool routing for CNC thermal cutting machines is sometimes reduced. Technological requirements bound to thermal fields distribution during cutting process are of great importance when developing algorithms for this task solution. These requirements give rise to some specific constraints for GTSP. This paper provides a mathematical formulation for the problem of thermal fields calculating during metal sheet thermal cutting. Corresponding algorithm with its programmatic implementation is considered. The mathematical model allowing taking such constraints into account considering other routing problems is discussed either.

Acquisition of business intelligence from human experience in route planning

NASA Astrophysics Data System (ADS)

Bello Orgaz, Gema; Barrero, David F.; R-Moreno, María D.; Camacho, David

2015-04-01

The logistic sector raises a number of highly challenging problems. Probably one of the most important ones is the shipping planning, i.e. plan the routes that the shippers have to follow to deliver the goods. In this article, we present an artificial intelligence-based solution that has been designed to help a logistic company to improve its routes planning process. In order to achieve this goal, the solution uses the knowledge acquired by the company drivers to propose optimised routes. Hence, the proposed solution gathers the experience of the drivers, processes it and optimises the delivery process. The solution uses data mining to extract knowledge from the company information systems and prepares it for analysis with a case-based reasoning (CBR) algorithm. The CBR obtains critical business intelligence knowledge from the drivers experience that is needed by the planner. The design of the routes is done by a genetic algorithm that, given the processed information, optimises the routes following several objectives, such as minimise the distance or time. Experimentation shows that the proposed approach is able to find routes that improve, on average, the routes made by the human experts.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

AVQS: Attack Route-Based Vulnerability Quantification Scheme for Smart Grid

PubMed Central

Lim, Hyunwoo; Lee, Seokjun; Shon, Taeshik

2014-01-01

A smart grid is a large, consolidated electrical grid system that includes heterogeneous networks and systems. Based on the data, a smart grid system has a potential security threat in its network connectivity. To solve this problem, we develop and apply a novel scheme to measure the vulnerability in a smart grid domain. Vulnerability quantification can be the first step in security analysis because it can help prioritize the security problems. However, existing vulnerability quantification schemes are not suitable for smart grid because they do not consider network vulnerabilities. We propose a novel attack route-based vulnerability quantification scheme using a network vulnerability score and an end-to-end security score, depending on the specific smart grid network environment to calculate the vulnerability score for a particular attack route. To evaluate the proposed approach, we derive several attack scenarios from the advanced metering infrastructure domain. The experimental results of the proposed approach and the existing common vulnerability scoring system clearly show that we need to consider network connectivity for more optimized vulnerability quantification. PMID:25152923

Does Calculation or Word-Problem Instruction Provide A Stronger Route to Pre-Algebraic Knowledge?

PubMed Central

Fuchs, Lynn S.; Powell, Sarah R.; Cirino, Paul T.; Schumacher, Robin F.; Marrin, Sarah; Hamlett, Carol L.; Fuchs, Douglas; Compton, Donald L.; Changas, Paul C.

2014-01-01

The focus of this study was connections among 3 aspects of mathematical cognition at 2nd grade: calculations, word problems, and pre-algebraic knowledge. We extended the literature, which is dominated by correlational work, by examining whether intervention conducted on calculations or word problems contributes to improved performance in the other domain and whether intervention in either or both domains contributes to pre-algebraic knowledge. Participants were 1102 children in 127 2nd-grade classrooms in 25 schools. Teachers were randomly assigned to 3 conditions: calculation intervention, word-problem intervention, and business-as-usual control. Intervention, which lasted 17 weeks, was designed to provide research-based linkages between arithmetic calculations or arithmetic word problems (depending on condition) to pre-algebraic knowledge. Multilevel modeling suggested calculation intervention improved calculation but not word-problem outcomes; word-problem intervention enhanced word-problem but not calculation outcomes; and word-problem intervention provided a stronger route than calculation intervention to pre-algebraic knowledge. PMID:25541565

Mathematical simulation for compensation capacities area of pipeline routes in ship systems

NASA Astrophysics Data System (ADS)

Ngo, G. V.; Sakhno, K. N.

2018-05-01

In this paper, the authors considered the problem of manufacturability’s enhancement of ship systems pipeline at the designing stage. The analysis of arrangements and possibilities for compensation of deviations for pipeline routes has been carried out. The task was set to produce the “fit pipe” together with the rest of the pipes in the route. It was proposed to compensate for deviations by movement of the pipeline route during pipe installation and to calculate maximum values of these displacements in the analyzed path. Theoretical bases of deviation compensation for pipeline routes using rotations of parallel section pairs of pipes are assembled. Mathematical and graphical simulations of compensation area capacities of pipeline routes with various configurations are completed. Prerequisites have been created for creating an automated program that will allow one to determine values of the compensatory capacities area for pipeline routes and to assign quantities of necessary allowances.

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

PubMed

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

Genetic algorithms for the vehicle routing problem

NASA Astrophysics Data System (ADS)

Volna, Eva

2016-06-01

The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization tasks. This problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. Evolutionary algorithms are general iterative algorithms for combinatorial optimization. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. This problem is known to be NP-hard; hence many heuristic procedures for its solution have been suggested. For such problems it is often desirable to obtain approximate solutions, so they can be found fast enough and are sufficiently accurate for the purpose. In this paper we have performed an experimental study that indicates the suitable use of genetic algorithms for the vehicle routing problem.

Capacitated arc routing problem and its extensions in waste collection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fadzli, Mohammad; Najwa, Nurul; Luis, Martino

2015-05-15

Capacitated arc routing problem (CARP) is the youngest generation of graph theory that focuses on solving the edge/arc routing for optimality. Since many years, operational research devoted to CARP counterpart, known as vehicle routing problem (VRP), which does not fit to several real cases such like waste collection problem and road maintenance. In this paper, we highlighted several extensions of capacitated arc routing problem (CARP) that represents the real-life problem of vehicle operation in waste collection. By purpose, CARP is designed to find a set of routes for vehicles that satisfies all pre-setting constraints in such that all vehicles mustmore » start and end at a depot, service a set of demands on edges (or arcs) exactly once without exceeding the capacity, thus the total fleet cost is minimized. We also addressed the differentiation between CARP and VRP in waste collection. Several issues have been discussed including stochastic demands and time window problems in order to show the complexity and importance of CARP in the related industry. A mathematical model of CARP and its new version is presented by considering several factors such like delivery cost, lateness penalty and delivery time.« less

Optimization-based channel constrained data aggregation routing algorithms in multi-radio wireless sensor networks.

PubMed

Yen, Hong-Hsu

2009-01-01

In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers as the link arc weight, the optimization-based heuristics are proposed to get energy-efficient data aggregation tree with better resource (channel and radio) utilization. From the computational experiments, the proposed optimization-based approach is superior to existing heuristics under all tested cases.

Sigma Routing Metric for RPL Protocol.

PubMed

Sanmartin, Paul; Rojas, Aldo; Fernandez, Luis; Avila, Karen; Jabba, Daladier; Valle, Sebastian

2018-04-21

This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.

Sigma Routing Metric for RPL Protocol

PubMed Central

Rojas, Aldo; Fernandez, Luis

2018-01-01

This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption. PMID:29690524

The integrated model for solving the single-period deterministic inventory routing problem

NASA Astrophysics Data System (ADS)

Rahim, Mohd Kamarul Irwan Abdul; Abidin, Rahimi; Iteng, Rosman; Lamsali, Hendrik

2016-08-01

This paper discusses the problem of efficiently managing inventory and routing problems in a two-level supply chain system. Vendor Managed Inventory (VMI) policy is an integrating decisions between a supplier and his customers. We assumed that the demand at each customer is stationary and the warehouse is implementing a VMI. The objective of this paper is to minimize the inventory and the transportation costs of the customers for a two-level supply chain. The problem is to determine the delivery quantities, delivery times and routes to the customers for the single-period deterministic inventory routing problem (SP-DIRP) system. As a result, a linear mixed-integer program is developed for the solutions of the SP-DIRP problem.

On the multiple depots vehicle routing problem with heterogeneous fleet capacity and velocity

NASA Astrophysics Data System (ADS)

Hanum, F.; Hartono, A. P.; Bakhtiar, T.

2018-03-01

This current manuscript concerns with the optimization problem arising in a route determination of products distribution. The problem is formulated in the form of multiple depots and time windowed vehicle routing problem with heterogeneous capacity and velocity of fleet. Model includes a number of constraints such as route continuity, multiple depots availability and serving time in addition to generic constraints. In dealing with the unique feature of heterogeneous velocity, we generate a number of velocity profiles along the road segments, which then converted into traveling-time tables. An illustrative example of rice distribution among villages by bureau of logistics is provided. Exact approach is utilized to determine the optimal solution in term of vehicle routes and starting time of service.

Traffic routing for multicomputer networks with virtual cut-through capability

NASA Technical Reports Server (NTRS)

Kandlur, Dilip D.; Shin, Kang G.

1992-01-01

Consideration is given to the problem of selecting routes for interprocess communication in a network with virtual cut-through capability, while balancing the network load and minimizing the number of times that a message gets buffered. An approach is proposed that formulates the route selection problem as a minimization problem with a link cost function that depends upon the traffic through the link. The form of this cost function is derived using the probability of establishing a virtual cut-through route. The route selection problem is shown to be NP-hard, and an algorithm is developed to incrementally reduce the cost by rerouting the traffic. The performance of this algorithm is exemplified by two network topologies: the hypercube and the C-wrapped hexagonal mesh.

A green vehicle routing problem with customer satisfaction criteria

NASA Astrophysics Data System (ADS)

Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.

2016-12-01

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

Research on the optimization of vehicle distribution routes in logistics enterprises

NASA Astrophysics Data System (ADS)

Fan, Zhigou; Ma, Mengkun

2018-01-01

With the rapid development of modern logistics, the vehicle routing problem has become one of the urgent problems in the logistics industry. The rationality of distribution route planning directly affects the efficiency and quality of logistics distribution. This paper first introduces the definition of logistics distribution and the three methods of optimizing the distribution routes, and then analyzes the current vehicle distribution route by using a representative example, finally puts forward the optimization schemes of logistics distribution route.

Distributed Efficient Similarity Search Mechanism in Wireless Sensor Networks

PubMed Central

Ahmed, Khandakar; Gregory, Mark A.

2015-01-01

The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes lack optimization for similarity queries of events. In this paper, a DCS scheme with metric based similarity searching (DCSMSS) is proposed. DCSMSS takes motivation from vector distance index, called iDistance, in order to transform the issue of similarity searching into the problem of an interval search in one dimension. In addition, a sector based distance routing algorithm is used to efficiently route messages. Extensive simulation results reveal that DCSMSS is highly efficient and significantly outperforms previous approaches in processing similarity search queries. PMID:25751081

Parallel optimization algorithm for drone inspection in the building industry

NASA Astrophysics Data System (ADS)

Walczyński, Maciej; BoŻejko, Wojciech; Skorupka, Dariusz

2017-07-01

In this paper we present an approach for Vehicle Routing Problem with Drones (VRPD) in case of building inspection from the air. In autonomic inspection process there is a need to determine of the optimal route for inspection drone. This is especially important issue because of the very limited flight time of modern multicopters. The method of determining solutions for Traveling Salesman Problem(TSP), described in this paper bases on Parallel Evolutionary Algorithm (ParEA)with cooperative and independent approach for communication between threads. This method described first by Bożejko and Wodecki [1] bases on the observation that if exists some number of elements on certain positions in a number of permutations which are local minima, then those elements will be in the same position in the optimal solution for TSP problem. Numerical experiments were made on BEM computational cluster with using MPI library.

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

NASA Astrophysics Data System (ADS)

Chen, Xianshun; Feng, Liang; Ong, Yew Soon

2012-07-01

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

Introducing the MCHF/OVRP/SDMP: Multicapacitated/Heterogeneous Fleet/Open Vehicle Routing Problems with Split Deliveries and Multiproducts

PubMed Central

Yilmaz Eroglu, Duygu; Caglar Gencosman, Burcu; Cavdur, Fatih; Ozmutlu, H. Cenk

2014-01-01

In this paper, we analyze a real-world OVRP problem for a production company. Considering real-world constrains, we classify our problem as multicapacitated/heterogeneous fleet/open vehicle routing problem with split deliveries and multiproduct (MCHF/OVRP/SDMP) which is a novel classification of an OVRP. We have developed a mixed integer programming (MIP) model for the problem and generated test problems in different size (10–90 customers) considering real-world parameters. Although MIP is able to find optimal solutions of small size (10 customers) problems, when the number of customers increases, the problem gets harder to solve, and thus MIP could not find optimal solutions for problems that contain more than 10 customers. Moreover, MIP fails to find any feasible solution of large-scale problems (50–90 customers) within time limits (7200 seconds). Therefore, we have developed a genetic algorithm (GA) based solution approach for large-scale problems. The experimental results show that the GA based approach reaches successful solutions with 9.66% gap in 392.8 s on average instead of 7200 s for the problems that contain 10–50 customers. For large-scale problems (50–90 customers), GA reaches feasible solutions of problems within time limits. In conclusion, for the real-world applications, GA is preferable rather than MIP to reach feasible solutions in short time periods. PMID:25045735

Dynamic airspace configuration algorithms for next generation air transportation system

NASA Astrophysics Data System (ADS)

Wei, Jian

The National Airspace System (NAS) is under great pressure to safely and efficiently handle the record-high air traffic volume nowadays, and will face even greater challenge to keep pace with the steady increase of future air travel demand, since the air travel demand is projected to increase to two to three times the current level by 2025. The inefficiency of traffic flow management initiatives causes severe airspace congestion and frequent flight delays, which cost billions of economic losses every year. To address the increasingly severe airspace congestion and delays, the Next Generation Air Transportation System (NextGen) is proposed to transform the current static and rigid radar based system to a dynamic and flexible satellite based system. New operational concepts such as Dynamic Airspace Configuration (DAC) have been under development to allow more flexibility required to mitigate the demand-capacity imbalances in order to increase the throughput of the entire NAS. In this dissertation, we address the DAC problem in the en route and terminal airspace under the framework of NextGen. We develop a series of algorithms to facilitate the implementation of innovative concepts relevant with DAC in both the en route and terminal airspace. We also develop a performance evaluation framework for comprehensive benefit analyses on different aspects of future sector design algorithms. First, we complete a graph based sectorization algorithm for DAC in the en route airspace, which models the underlying air route network with a weighted graph, converts the sectorization problem into the graph partition problem, partitions the weighted graph with an iterative spectral bipartition method, and constructs the sectors from the partitioned graph. The algorithm uses a graph model to accurately capture the complex traffic patterns of the real flights, and generates sectors with high efficiency while evenly distributing the workload among the generated sectors. We further improve the robustness and efficiency of the graph based DAC algorithm by incorporating the Multilevel Graph Partitioning (MGP) method into the graph model, and develop a MGP based sectorization algorithm for DAC in the en route airspace. In a comprehensive benefit analysis, the performance of the proposed algorithms are tested in numerical simulations with Enhanced Traffic Management System (ETMS) data. Simulation results demonstrate that the algorithmically generated sectorizations outperform the current sectorizations in different sectors for different time periods. Secondly, based on our experience with DAC in the en route airspace, we further study the sectorization problem for DAC in the terminal airspace. The differences between the en route and terminal airspace are identified, and their influence on the terminal sectorization is analyzed. After adjusting the graph model to better capture the unique characteristics of the terminal airspace and the requirements of terminal sectorization, we develop a graph based geometric sectorization algorithm for DAC in the terminal airspace. Moreover, the graph based model is combined with the region based sector design method to better handle the complicated geometric and operational constraints in the terminal sectorization problem. In the benefit analysis, we identify the contributing factors to terminal controller workload, define evaluation metrics, and develop a bebefit analysis framework for terminal sectorization evaluation. With the evaluation framework developed, we demonstrate the improvements on the current sectorizations with real traffic data collected from several major international airports in the U.S., and conduct a detailed analysis on the potential benefits of dynamic reconfiguration in the terminal airspace. Finally, in addition to the research on the macroscopic behavior of a large number of aircraft, we also study the dynamical behavior of individual aircraft from the perspective of traffic flow management. We formulate the mode-confusion problem as hybrid estimation problem, and develop a state estimation algorithm for the linear hybrid system with continuous-state-dependent transitions based on sparse observations. We also develop an estimated time of arrival prediction algorithm based on the state-dependent transition hybrid estimation algorithm, whose performance is demonstrated with simulations on the landing procedure following the Continuous Descend Approach (CDA) profile.

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, D.; Zhang, W. Y.

2017-08-01

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

Optimization for routing vehicles of seafood product transportation

NASA Astrophysics Data System (ADS)

Soenandi, I. A.; Juan, Y.; Budi, M.

2017-12-01

Recently, increasing usage of marine products is creating new challenges for businesses of marine products in terms of transportation that used to carry the marine products like seafood to the main warehouse. This can be a problem if the carrier fleet is limited, and there are time constraints in terms of the freshness of the marine product. There are many ways to solve this problem, including the optimization of routing vehicles. In this study, this strategy is to implement in the marine product business in Indonesia with such an expected arrangement of the company to optimize routing problem in transportation with time and capacity windows. Until now, the company has not used the scientific method to manage the routing of their vehicle from warehouse to the location of marine products source. This study will solve a stochastic Vehicle Routing Problems (VRP) with time and capacity windows by using the comparison of six methods and looking the best results for the optimization, in this situation the company could choose the best method, in accordance with the existing condition. In this research, we compared the optimization with another method such as branch and bound, dynamic programming and Ant Colony Optimization (ACO). Finally, we get the best result after running ACO algorithm with existing travel time data. With ACO algorithm was able to reduce vehicle travel time by 3189.65 minutes, which is about 23% less than existing and based on consideration of the constraints of time within 2 days (including rest time for the driver) using 28 tons capacity of truck and the companies need two units of vehicles for transportation.

Effective bandwidth guaranteed routing schemes for MPLS traffic engineering

NASA Astrophysics Data System (ADS)

Wang, Bin; Jain, Nidhi

2001-07-01

In this work, we present online algorithms for dynamic routing bandwidth guaranteed label switched paths (LSPs) where LSP set-up requests (in terms of a pair of ingress and egress routers as well as its bandwidth requirement) arrive one by one and there is no a priori knowledge regarding future LSP set-up requests. In addition, we consider rerouting of LSPs in this work. Rerouting of LSPs has not been well studied in previous work on LSP routing. The need of LSP rerouting arises in a number of ways: occurrence of faults (link and/or node failures), re-optimization of existing LSPs' routes to accommodate traffic fluctuation, requests with higher priorities, and so on. We formulate the bandwidth guaranteed LSP routing with rerouting capability as a multi-commodity flow problem. The solution to this problem is used as the benchmark for comparing other computationally less costly algorithms studied in this paper. Furthermore, to more efficiently utilize the network resources, we propose online routing algorithms which route bandwidth demands over multiple paths at the ingress router to satisfy the customer requests while providing better service survivability. Traffic splitting and distribution over the multiple paths are carefully handled using table-based hashing schemes while the order of packets within a flow is preserved. Preliminary simulations are conducted to show the performance of different design choices and the effectiveness of the rerouting and multi-path routing algorithms in terms of LSP set-up request rejection probability and bandwidth blocking probability.

Efficient data communication protocols for wireless networks

NASA Astrophysics Data System (ADS)

Zeydan, Engin

In this dissertation, efficient decentralized algorithms are investigated for cost minimization problems in wireless networks. For wireless sensor networks, we investigate both the reduction in the energy consumption and throughput maximization problems separately using multi-hop data aggregation for correlated data in wireless sensor networks. The proposed algorithms exploit data redundancy using a game theoretic framework. For energy minimization, routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function used in routing takes into account distance, interference and in-network data aggregation. The proposed energy-efficient correlation-aware routing algorithm significantly reduces the energy consumption in the network and converges in a finite number of steps iteratively. For throughput maximization, we consider both the interference distribution across the network and correlation between forwarded data when establishing routes. Nodes along each route are chosen to minimize the interference impact in their neighborhood and to maximize the in-network data aggregation. The resulting network topology maximizes the global network throughput and the algorithm is guaranteed to converge with a finite number of steps using best response dynamics. For multiple antenna wireless ad-hoc networks, we present distributed cooperative and regret-matching based learning schemes for joint transmit beanformer and power level selection problem for nodes operating in multi-user interference environment. Total network transmit power is minimized while ensuring a constant received signal-to-interference and noise ratio at each receiver. In cooperative and regret-matching based power minimization algorithms, transmit beanformers are selected from a predefined codebook to minimize the total power. By selecting transmit beamformers judiciously and performing power adaptation, the cooperative algorithm is shown to converge to pure strategy Nash equilibrium with high probability throughout the iterations in the interference impaired network. On the other hand, the regret-matching learning algorithm is noncooperative and requires minimum amount of overhead. The proposed cooperative and regret-matching based distributed algorithms are also compared with centralized solutions through simulation results.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.

PubMed

Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

2015-01-01

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks.

PubMed

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-10-09

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

PubMed Central

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-01-01

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. PMID:28991200

U-Access: a web-based system for routing pedestrians of differing abilities

NASA Astrophysics Data System (ADS)

Sobek, Adam D.; Miller, Harvey J.

2006-09-01

For most people, traveling through urban and built environments is straightforward. However, for people with physical disabilities, even a short trip can be difficult and perhaps impossible. This paper provides the design and implementation of a web-based system for the routing and prescriptive analysis of pedestrians with different physical abilities within built environments. U-Access, as a routing tool, provides pedestrians with the shortest feasible route with respect to one of three differing ability levels, namely, peripatetic (unaided mobility), aided mobility (mobility with the help of a cane, walker or crutches) and wheelchair users. U-Access is also an analytical tool that can help identify obstacles in built environments that create routing discrepancies among pedestrians with different physical abilities. This paper discusses the system design, including database, algorithm and interface specifications, and technologies for efficiently delivering results through the World Wide Web (WWW). This paper also provides an illustrative example of a routing problem and an analytical evaluation of the existing infrastructure which identifies the obstacles that pose the greatest discrepancies between physical ability levels. U-Access was evaluated by wheelchair users and route experts from the Center for Disability Services at The University of Utah, USA.

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Developing cross entropy genetic algorithm for solving Two-Dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP)

NASA Astrophysics Data System (ADS)

Paramestha, D. L.; Santosa, B.

2018-04-01

Two-dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP) is a combination of Heterogeneous Fleet VRP and a packing problem well-known as Two-Dimensional Bin Packing Problem (BPP). 2L-HFVRP is a Heterogeneous Fleet VRP in which these costumer demands are formed by a set of two-dimensional rectangular weighted item. These demands must be served by a heterogeneous fleet of vehicles with a fix and variable cost from the depot. The objective function 2L-HFVRP is to minimize the total transportation cost. All formed routes must be consistent with the capacity and loading process of the vehicle. Sequential and unrestricted scenarios are considered in this paper. We propose a metaheuristic which is a combination of the Genetic Algorithm (GA) and the Cross Entropy (CE) named Cross Entropy Genetic Algorithm (CEGA) to solve the 2L-HFVRP. The mutation concept on GA is used to speed up the algorithm CE to find the optimal solution. The mutation mechanism was based on local improvement (2-opt, 1-1 Exchange, and 1-0 Exchange). The probability transition matrix mechanism on CE is used to avoid getting stuck in the local optimum. The effectiveness of CEGA was tested on benchmark instance based 2L-HFVRP. The result of experiments shows a competitive result compared with the other algorithm.

On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

NASA Astrophysics Data System (ADS)

Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

2016-05-01

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

Nudging socially isolated people towards well-being with the 'Happiness Route': design of a randomized controlled trial for the evaluation of a happiness-based intervention.

PubMed

Weiss, Laura A; Westerhof, Gerben J; Bohlmeijer, Ernst T

2013-09-20

The Happiness Route is an innovative intervention that uses a happiness-based approach for people with an accumulation of risk factors for low well-being: socially isolated people with health impairments and a low socioeconomic status. The goal of this intervention is to improve well-being by engaging participants in intrinsically motivated activities with methods from positive psychology. We hypothesize that the primary outcome measure, emotional, social and psychological well-being of participants of the Happiness Route, will increase in comparison to the traditional and commonly-used problem-based approach. Secondary outcome measures are health-related quality of life, psychosocial functioning and health care consumption. Participants will be socially isolated people with health problems and a low socioeconomic status. Participants will be recruited in ten Dutch communities and candidates will be signed up by intermediaries, professionals from the health and social sector. Randomly assigned, half of the participants will follow the Happiness Route and half of the participants will follow the active, problem-focused control group 'Customized Care'. In total, 256 participants will be included. In both conditions, participants will receive counseling sessions from trained counselors. In the control group, participants will talk about their problems and the care they get and counselors help to optimize their care. In the Happiness Route, the counselor ask questions such as "How do you want to live your life?". The intervention helps people to find their 'passion', i.e., a positive goal-engaged and intrinsically motivated activity. It enables them to follow their passion through by a once-only personal happiness budget (maximal €500). We use well-validated and reliable questionnaires to measure primary and secondary outcome measures at baseline, directly after the intervention and at a nine-month follow-up. Shortcomings of earlier intervention studies in positive psychology will be tackled with this study, such as having a target group who is especially vulnerable for low well-being. The practice-based setting is especially interesting, as it can give valuable insights in how positive psychology interventions work in practice, but can also give rise to several challenges. Dutch Trial Register, trial registration number TC=3377NTR.http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3377.

Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling

NASA Astrophysics Data System (ADS)

Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina

2018-01-01

The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.

Inventory slack routing application in emergency logistics and relief distributions.

PubMed

Yang, Xianfeng; Hao, Wei; Lu, Yang

2018-01-01

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches.

Inventory slack routing application in emergency logistics and relief distributions

PubMed Central

Yang, Xianfeng; Lu, Yang

2018-01-01

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches. PMID:29902196

Application of modern control theory to scheduling and path-stretching maneuvers of aircraft in the near terminal area

NASA Technical Reports Server (NTRS)

Athans, M.

1974-01-01

A design concept of the dynamic control of aircraft in the near terminal area is discussed. An arbitrary set of nominal air routes, with possible multiple merging points, all leading to a single runway, is considered. The system allows for the automated determination of acceleration/deceleration of aircraft along the nominal air routes, as well as for the automated determination of path-stretching delay maneuvers. In addition to normal operating conditions, the system accommodates: (1) variable commanded separations over the outer marker to allow for takeoffs and between successive landings and (2) emergency conditions under which aircraft in distress have priority. The system design is based on a combination of three distinct optimal control problems involving a standard linear-quadratic problem, a parameter optimization problem, and a minimum-time rendezvous problem.

Freight distribution problems in congested urban areas : fast and effective solution procedures to time-dependent vehicle routing problems

DOT National Transportation Integrated Search

2011-01-01

Congestion is a common phenomenon in all medium to large cities of the world. Reliability of freight movement in urban areas is an important : issue to manufacturing or service companies whose operation is based in just-in-time approaches. These comp...

Using Approximate Dynamic Programming to Solve the Stochastic Demand Military Inventory Routing Problem with Direct Delivery

DTIC Science & Technology

due to the dangers of utilizing convoy operations. However, enemy actions, austere conditions, and inclement weather pose a significant risk to a...squares temporal differencing for policy evaluation. We construct a representative problem instance based on an austere combat environment in order to

Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks

NASA Technical Reports Server (NTRS)

Dudukovich, Rachel; Raible, Daniel E.

2016-01-01

The challenges of data processing, transmission scheduling and routing within a space network present a multi-criteria optimization problem. Long delays, intermittent connectivity, asymmetric data rates and potentially high error rates make traditional networking approaches unsuitable. The delay tolerant networking architecture and protocols attempt to mitigate many of these issues, yet transmission scheduling is largely manually configured and routes are determined by a static contact routing graph. A high level of variability exists among the requirements and environmental characteristics of different missions, some of which may allow for the use of more opportunistic routing methods. In all cases, resource allocation and constraints must be balanced with the optimization of data throughput and quality of service. Much work has been done researching routing techniques for terrestrial-based challenged networks in an attempt to optimize contact opportunities and resource usage. This paper examines several popular methods to determine their potential applicability to space networks.

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

DTIC Science & Technology

2015-01-01

programming formulation of traveling salesman problems , Journal of the ACM, 7(4), 326-329. Montemanni, R., Gambardella, L. M., Rizzoli, A.E., Donati. A.V... salesman problem . BioSystem, 43(1), 73-81. Dror, M., Trudeau, P., 1989. Savings by split delivery routing. Transportation Science, 23, 141- 145. Dror, M...An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to solve the Split Delivery Vehicle Routing Problem Authors: Gautham Rajappa

Using Ant Colony Optimization for Routing in VLSI Chips

NASA Astrophysics Data System (ADS)

Arora, Tamanna; Moses, Melanie

2009-04-01

Rapid advances in VLSI technology have increased the number of transistors that fit on a single chip to about two billion. A frequent problem in the design of such high performance and high density VLSI layouts is that of routing wires that connect such large numbers of components. Most wire-routing problems are computationally hard. The quality of any routing algorithm is judged by the extent to which it satisfies routing constraints and design objectives. Some of the broader design objectives include minimizing total routed wire length, and minimizing total capacitance induced in the chip, both of which serve to minimize power consumed by the chip. Ant Colony Optimization algorithms (ACO) provide a multi-agent framework for combinatorial optimization by combining memory, stochastic decision and strategies of collective and distributed learning by ant-like agents. This paper applies ACO to the NP-hard problem of finding optimal routes for interconnect routing on VLSI chips. The constraints on interconnect routing are used by ants as heuristics which guide their search process. We found that ACO algorithms were able to successfully incorporate multiple constraints and route interconnects on suite of benchmark chips. On an average, the algorithm routed with total wire length 5.5% less than other established routing algorithms.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors

PubMed Central

Desai, Prajakta; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies. PMID:28792513

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

PubMed

Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks

PubMed Central

Robinson, Y. Harold; Rajaram, M.

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966

An Elementary Algorithm for Autonomous Air Terminal Merging and Interval Management

NASA Technical Reports Server (NTRS)

White, Allan L.

2017-01-01

A central element of air traffic management is the safe merging and spacing of aircraft during the terminal area flight phase. This paper derives and examines an algorithm for the merging and interval managing problem for Standard Terminal Arrival Routes. It describes a factor analysis for performance based on the distribution of arrivals, the operating period of the terminal, and the topology of the arrival routes; then presents results from a performance analysis and from a safety analysis for a realistic topology based on typical routes for a runway at Phoenix International Airport. The heart of the safety analysis is a statistical derivation on how to conduct a safety analysis for a local simulation when the safety requirement is given for the entire airspace.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.

PubMed

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem

PubMed Central

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA. PMID:26167171

Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows

PubMed Central

Jawarneh, Sana; Abdullah, Salwani

2015-01-01

This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon’s 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results. PMID:26132158

Cost-aware request routing in multi-geography cloud data centres using software-defined networking

NASA Astrophysics Data System (ADS)

Yuan, Haitao; Bi, Jing; Li, Bo Hu; Tan, Wei

2017-03-01

Current geographically distributed cloud data centres (CDCs) require gigantic energy and bandwidth costs to provide multiple cloud applications to users around the world. Previous studies only focus on energy cost minimisation in distributed CDCs. However, a CDC provider needs to deliver gigantic data between users and distributed CDCs through internet service providers (ISPs). Geographical diversity of bandwidth and energy costs brings a highly challenging problem of how to minimise the total cost of a CDC provider. With the recently emerging software-defined networking, we study the total cost minimisation problem for a CDC provider by exploiting geographical diversity of energy and bandwidth costs. We formulate the total cost minimisation problem as a mixed integer non-linear programming (MINLP). Then, we develop heuristic algorithms to solve the problem and to provide a cost-aware request routing for joint optimisation of the selection of ISPs and the number of servers in distributed CDCs. Besides, to tackle the dynamic workload in distributed CDCs, this article proposes a regression-based workload prediction method to obtain future incoming workload. Finally, this work evaluates the cost-aware request routing by trace-driven simulation and compares it with the existing approaches to demonstrate its effectiveness.

Optimization of municipal waste collection scheduling and routing using vehicle assignment problem (case study of Surabaya city waste collection)

NASA Astrophysics Data System (ADS)

Ramdhani, M. N.; Baihaqi, I.; Siswanto, N.

2018-04-01

Waste collection and disposal become a major problem for many metropolitan cities. Growing population, limited vehicles, and increased road traffic make the waste transportation become more complex. Waste collection involves some key considerations, such as vehicle assignment, vehicle routes, and vehicle scheduling. In the scheduling process, each vehicle has a scheduled departure that serve each route. Therefore, vehicle’s assignments should consider the time required to finish one assigment on that route. The objective of this study is to minimize the number of vehicles needed to serve all routes by developing a mathematical model which uses assignment problem approach. The first step is to generated possible routes from the existing routes, followed by vehicle assignments for those certain routes. The result of the model shows fewer vehicles required to perform waste collection asa well as the the number of journeys that the vehicle to collect the waste to the landfill. The comparison of existing conditions with the model result indicates that the latter’s has better condition than the existing condition because each vehicle with certain route has an equal workload, all the result’s model has the maximum of two journeys for each route.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks

PubMed Central

Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

2015-01-01

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

Energy-Efficient Routing and Spectrum Assignment Algorithm with Physical-Layer Impairments Constraint in Flexible Optical Networks

NASA Astrophysics Data System (ADS)

Zhao, Jijun; Zhang, Nawa; Ren, Danping; Hu, Jinhua

2017-12-01

The recently proposed flexible optical network can provide more efficient accommodation of multiple data rates than the current wavelength-routed optical networks. Meanwhile, the energy efficiency has also been a hot topic because of the serious energy consumption problem. In this paper, the energy efficiency problem of flexible optical networks with physical-layer impairments constraint is studied. We propose a combined impairment-aware and energy-efficient routing and spectrum assignment (RSA) algorithm based on the link availability, in which the impact of power consumption minimization on signal quality is considered. By applying the proposed algorithm, the connection requests are established on a subset of network topology, reducing the number of transitions from sleep to active state. The simulation results demonstrate that our proposed algorithm can improve the energy efficiency and spectrum resources utilization with the acceptable blocking probability and average delay.

A Novel Discrete Differential Evolution Algorithm for the Vehicle Routing Problem in B2C E-Commerce

NASA Astrophysics Data System (ADS)

Xia, Chao; Sheng, Ying; Jiang, Zhong-Zhong; Tan, Chunqiao; Huang, Min; He, Yuanjian

2015-12-01

In this paper, a novel discrete differential evolution (DDE) algorithm is proposed to solve the vehicle routing problems (VRP) in B2C e-commerce, in which VRP is modeled by the incomplete graph based on the actual urban road system. First, a variant of classical VRP is described and a mathematical programming model for the variant is given. Second, the DDE is presented, where individuals are represented as the sequential encoding scheme, and a novel reparation operator is employed to repair the infeasible solutions. Furthermore, a FLOYD operator for dealing with the shortest route is embedded in the proposed DDE. Finally, an extensive computational study is carried out in comparison with the predatory search algorithm and genetic algorithm, and the results show that the proposed DDE is an effective algorithm for VRP in B2C e-commerce.

On the preventive management of sediment-related sewer blockages: a combined maintenance and routing optimization approach.

PubMed

Fontecha, John E; Akhavan-Tabatabaei, Raha; Duque, Daniel; Medaglia, Andrés L; Torres, María N; Rodríguez, Juan Pablo

In this work we tackle the problem of planning and scheduling preventive maintenance (PM) of sediment-related sewer blockages in a set of geographically distributed sites that are subject to non-deterministic failures. To solve the problem, we extend a combined maintenance and routing (CMR) optimization approach which is a procedure based on two components: (a) first a maintenance model is used to determine the optimal time to perform PM operations for each site and second (b) a mixed integer program-based split procedure is proposed to route a set of crews (e.g., sewer cleaners, vehicles equipped with winches or rods and dump trucks) in order to perform PM operations at a near-optimal minimum expected cost. We applied the proposed CMR optimization approach to two (out of five) operative zones in the city of Bogotá (Colombia), where more than 100 maintenance operations per zone must be scheduled on a weekly basis. Comparing the CMR against the current maintenance plan, we obtained more than 50% of cost savings in 90% of the sites.

A capacitated vehicle routing problem with order available time in e-commerce industry

NASA Astrophysics Data System (ADS)

Liu, Ling; Li, Kunpeng; Liu, Zhixue

2017-03-01

In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.

Selective randomized load balancing and mesh networks with changing demands

NASA Astrophysics Data System (ADS)

Shepherd, F. B.; Winzer, P. J.

2006-05-01

We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

NASA Astrophysics Data System (ADS)

Sun, Xiuqiao; Wang, Jian

2018-07-01

Freeway service patrol (FSP), is considered to be an effective method for incident management and can help transportation agency decision-makers alter existing route coverage and fleet allocation. This paper investigates the FSP problem of patrol routing design and fleet allocation, with the objective of minimizing the overall average incident response time. While the simulated annealing (SA) algorithm and its improvements have been applied to solve this problem, they often become trapped in local optimal solution. Moreover, the issue of searching efficiency remains to be further addressed. In this paper, we employ the genetic algorithm (GA) and SA to solve the FSP problem. To maintain population diversity and avoid premature convergence, niche strategy is incorporated into the traditional genetic algorithm. We also employ elitist strategy to speed up the convergence. Numerical experiments have been conducted with the help of the Sioux Falls network. Results show that the GA slightly outperforms the dual-based greedy (DBG) algorithm, the very large-scale neighborhood searching (VLNS) algorithm, the SA algorithm and the scenario algorithm.

Unique Applications for Artificial Neural Networks. Phase 1

DTIC Science & Technology

1991-08-08

significance. For the VRP, a problem that has received considerable attention in the literature, the new NGO-VRP methodology generates better solutions...represent the stop assignments of each route. The effect of the genetic recombinations is to make simple local exchanges to the relative positions of the...technique for representing a computer-based associative memory [Arbib, 1987]. In our routing system, the basic job of the neural network system is to accept

Optimization of OSPF Routing in IP Networks

NASA Astrophysics Data System (ADS)

Bley, Andreas; Fortz, Bernard; Gourdin, Eric; Holmberg, Kaj; Klopfenstein, Olivier; Pióro, Michał; Tomaszewski, Artur; Ümit, Hakan

The Internet is a huge world-wide packet switching network comprised of more than 13,000 distinct subnetworks, referred to as Autonomous Systems (ASs) autonomous system AS . They all rely on the Internet Protocol (IP) internet protocol IP for transport of packets across the network. And most of them use shortest path routing protocols shortest path routing!protocols , such as OSPF or IS-IS, to control the routing of IP packets routing!of IP packets within an AS. The idea of the routing is extremely simple — every packet is forwarded on IP links along the shortest route between its source and destination nodes of the AS. The AS network administrator can manage the routing of packets in the AS by supplying the so-called administrative weights of IP links, which specify the link lengths that are used by the routing protocols for their shortest path computations. The main advantage of the shortest path routing policy is its simplicity, allowing for little administrative overhead. From the network engineering perspective, however, shortest path routing can pose problems in achieving satisfactory traffic handling efficiency. As all routing paths depend on the same routing metric routing!metric , it is not possible to configure the routing paths for the communication demands between different pairs of nodes explicitly or individually; the routing can be controlled only indirectly and only as a whole by modifying the routing metric. Thus, one of the main tasks when planning such networks is to find administrative link weights that induce a globally efficient traffic routing traffic!routing configuration of an AS. It turns out that this task leads to very difficult mathematical optimization problems. In this chapter, we discuss and describe exact integer programming models and solution approaches as well as practically efficient smart heuristics for such shortest path routing problems shortest path routing!problems .

Using Approximate Dynamic Programming to Solve the Military Inventory Routing Problem with Direct Delivery

DTIC Science & Technology

2015-03-26

benefit by no longer having to allocate resources to inventory management . When the inventory routing problem is solved , three key decisions are made at...industries rely on the transportation and manage – ment of goods. To aid in understanding the formulation and techniques for solving the military inventory...Using Approximate Dynamic Programming to Solve the Military Inventory Routing Problem with Direct Delivery THESIS MARCH 2015 Rebekah S. McKenna

En route Spacing Tool: Efficient Conflict-free Spacing to Flow-Restricted Airspace

NASA Technical Reports Server (NTRS)

Green, S.

1999-01-01

This paper describes the Air Traffic Management (ATM) problem within the U.S. of flow-restricted en route airspace, an assessment of its impact on airspace users, and a set of near-term tools and procedures to resolve the problem. The FAA is committed, over the next few years, to deploy the first generation of modem ATM decision support tool (DST) technology under the Free-Flight Phase-1 (FFp1) program. The associated en route tools include the User Request Evaluation Tool (URET) and the Traffic Management Advisor (TMA). URET is an initial conflict probe (ICP) capability that assists controllers with the detection and resolution of conflicts in en route airspace. TMA orchestrates arrivals transitioning into high-density terminal airspace by providing controllers with scheduled times of arrival (STA) and delay feedback advisories to assist with STA conformance. However, these FFPl capabilities do not mitigate the en route Miles-In-Trail (MIT) restrictions that are dynamically applied to mitigate airspace congestion. National statistics indicate that en route facilities (Centers) apply Miles-In-Trail (MIT) restrictions for approximately 5000 hours per month. Based on results from this study, an estimated 45,000 flights are impacted by these restrictions each month. Current-day practices for implementing these restrictions result in additional controller workload and an economic impact of which the fuel penalty alone may approach several hundred dollars per flight. To mitigate much of the impact of these restrictions on users and controller workload, a DST and procedures are presented. The DST is based on a simple derivative of FFP1 technology that is designed to introduce a set of simple tools for flow-rate (spacing) conformance and integrate them with conflict-probe capabilities. The tool and associated algorithms are described based on a concept prototype implemented within the CTAS baseline in 1995. A traffic scenario is used to illustrate the controller's use of the tool, and potential display options are presented for future controller evaluation.

Improving the Air Mobility Command’s Air Refueler Route Building Capabilities

DTIC Science & Technology

2014-03-27

routing tool. Sundar and Rathinam [18] also study a traveling salesman version of the problem in the unmanned aerial vehicle realm. Their focus is on...constrained shortest path with fuel limitations. The objective is to minimize the distance traveled . Some aircraft routing problems involve...radius and network density their only limitations. 4 O’Rourke et al. [15] examine a traveling salesman version of aircraft routing in the unmanned aerial

An integer programming approach to a real-world recyclable waste collection problem in Argentina.

PubMed

Braier, Gustavo; Durán, Guillermo; Marenco, Javier; Wesner, Francisco

2017-05-01

This article reports on the use of mathematical programming techniques to optimise the routes of a recyclable waste collection system servicing Morón, a large municipality outside Buenos Aires, Argentina. The truck routing problem posed by the system is a particular case of the generalised directed open rural postman problem. An integer programming model is developed with a solving procedure built around a subtour-merging algorithm and the addition of subtour elimination constraints. The route solutions generated by the proposed methodology perform significantly better than the previously used, manually designed routes, the main improvement being that coverage of blocks within the municipality with the model solutions is 100% by construction, whereas with the manual routes as much as 16% of the blocks went unserviced. The model-generated routes were adopted by the municipality in 2014 and the national government is planning to introduce the methodology elsewhere in the country.

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment

PubMed Central

Wang, Liangmin

2018-01-01

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node’s transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical. PMID:29538314

3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment.

PubMed

Sohail, Muhammad; Wang, Liangmin

2018-03-14

Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics. The goal of future vehicular networks is to improve road safety, promote commercial or infotainment products and to reduce the traffic accidents. All these applications are based on the information exchange among nodes, so not only reliable data delivery but also the authenticity and credibility of the data itself are prerequisite. To cope with the aforementioned problem, trust management come up as promising candidate to conduct node's transaction and interaction management, which requires distributed mobile nodes cooperation for achieving design goals. In this paper, we propose a trust-based routing protocol i.e., 3VSR (Three Valued Secure Routing), which extends the widely used AODV (Ad hoc On-demand Distance Vector) routing protocol and employs the idea of Sensing Logic-based trust model to enhance the security solution of VANET (Vehicular Ad-Hoc Network). The existing routing protocol are mostly based on key or signature-based schemes, which off course increases computation overhead. In our proposed 3VSR, trust among entities is updated frequently by means of opinion derived from sensing logic due to vehicles random topologies. In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. Also by using trust recommendation message exchange, nodes are able to reduce computation and routing overhead. The simulated results shows that the proposed scheme is secure and practical.

Approximability of the d-dimensional Euclidean capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Khachay, Michael; Dubinin, Roman

2016-10-01

Capacitated Vehicle Routing Problem (CVRP) is the well known intractable combinatorial optimization problem, which remains NP-hard even in the Euclidean plane. Since the introduction of this problem in the middle of the 20th century, many researchers were involved into the study of its approximability. Most of the results obtained in this field are based on the well known Iterated Tour Partition heuristic proposed by M. Haimovich and A. Rinnoy Kan in their celebrated paper, where they construct the first Polynomial Time Approximation Scheme (PTAS) for the single depot CVRP in ℝ2. For decades, this result was extended by many authors to numerous useful modifications of the problem taking into account multiple depots, pick up and delivery options, time window restrictions, etc. But, to the best of our knowledge, almost none of these results go beyond the Euclidean plane. In this paper, we try to bridge this gap and propose a EPTAS for the Euclidean CVRP for any fixed dimension.

Switched Systems and Motion Coordination: Combinatorial Challenges

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.

2016-01-01

Problems of routing commercial air traffic in a terminal airspace encounter different constraints: separation assurance, aircraft performance limitations, regulations. The general setting of these problems is that of a switched control system. Such a system combines the differentiable motion of the aircraft with the combinatorial choices of choosing precedence when traffic routes merge and choosing branches when the routes diverge. This presentation gives an overview of the problem, the ATM context, related literature, and directions for future research.

Adaptive MANET multipath routing algorithm based on the simulated annealing approach.

PubMed

Kim, Sungwook

2014-01-01

Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.

Selective epidemic vaccination under the performant routing algorithms

NASA Astrophysics Data System (ADS)

Bamaarouf, O.; Alweimine, A. Ould Baba; Rachadi, A.; EZ-Zahraouy, H.

2018-04-01

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

Integrated Thermal Response Modeling System For Hypersonic Entry Vehicles

NASA Technical Reports Server (NTRS)

Chen, Y.-K.; Milos, F. S.; Partridge, Harry (Technical Monitor)

2000-01-01

We describe all extension of the Markov decision process model in which a continuous time dimension is included ill the state space. This allows for the representation and exact solution of a wide range of problems in which transitions or rewards vary over time. We examine problems based on route planning with public transportation and telescope observation scheduling.

Exact Solutions to Time-dependent Mdps

NASA Technical Reports Server (NTRS)

Boyan, Justin A.; Littman, Michael L.

2000-01-01

We describe an extension of the Markov decision process model in which a continuous time dimension is included in the state space. This allows for the representation and exact solution of a wide range of problems in which transitions or rewards vary over time. We examine problems based on route planning with public transportation and telescope observation scheduling.

Research on vehicles and cargos matching model based on virtual logistics platform

NASA Astrophysics Data System (ADS)

Zhuang, Yufeng; Lu, Jiang; Su, Zhiyuan

2018-04-01

Highway less than truckload (LTL) transportation vehicles and cargos matching problem is a joint optimization problem of typical vehicle routing and loading, which is also a hot issue of operational research. This article based on the demand of virtual logistics platform, for the problem of the highway LTL transportation, the matching model of the idle vehicle and the transportation order is set up and the corresponding genetic algorithm is designed. Then the algorithm is implemented by Java. The simulation results show that the solution is satisfactory.

Routing and Addressing Problems in Large Metropolitan-Scale Internetworks. ISI Research Report.

ERIC Educational Resources Information Center

Finn, Gregory G.

This report discusses some of the problems and limitations in existing internetwork design for the connection of packet-switching networks of different technologies and presents an algorithm that has been shown to be suitable for internetworks of unbounded size. Using a new form of address and a flat routing mechanism called Cartesian routing,…

MODFLOW-based coupled surface water routing and groundwater-flow simulation

USGS Publications Warehouse

Hughes, Joseph D.; Langevin, Christian D.; White, Jeremy T.

2015-01-01

In this paper, we present a flexible approach for simulating one- and two-dimensional routing of surface water using a numerical surface water routing (SWR) code implicitly coupled to the groundwater-flow process in MODFLOW. Surface water routing in SWR can be simulated using a diffusive-wave approximation of the Saint-Venant equations and/or a simplified level-pool approach. SWR can account for surface water flow controlled by backwater conditions caused by small water-surface gradients or surface water control structures. A number of typical surface water control structures, such as culverts, weirs, and gates, can be represented, and it is possible to implement operational rules to manage surface water stages and streamflow. The nonlinear system of surface water flow equations formulated in SWR is solved by using Newton methods and direct or iterative solvers. SWR was tested by simulating the (1) Lal axisymmetric overland flow, (2) V-catchment, and (3) modified Pinder-Sauer problems. Simulated results for these problems compare well with other published results and indicate that SWR provides accurate results for surface water-only and coupled surface water/groundwater problems. Results for an application of SWR and MODFLOW to the Snapper Creek area of Miami-Dade County, Florida, USA are also presented and demonstrate the value of coupled surface water and groundwater simulation in managed, low-relief coastal settings.

Let the pigeon drive the bus: pigeons can plan future routes in a room.

PubMed

Gibson, Brett; Wilkinson, Matthew; Kelly, Debbie

2012-05-01

The task of determining an optimal route to several locations is called the traveling salesperson problem (TSP). The TSP has been used recently to examine spatial cognition in humans and non-human animals. It remains unclear whether or not the decision process of animals other than non-human primates utilizes rigid rule-based heuristics, or whether non-human animals are able to flexibly 'plan' future routes/behavior based on their knowledge of multiple locations. We presented pigeons in a One-way and Round-Trip group with TSPs that included two or three destinations (feeders) in a laboratory environment. The pigeons departed a start location, traveled to each feeder once before returning to a final destination. Pigeons weighed the proximity of the next location heavily, but appeared to plan ahead multiple steps when the travel costs for inefficient behavior appeared to increase. The results provide clear and strong evidence that animals other than primates are capable of planning sophisticated travel routes.

Coordinated Platoon Routing in a Metropolitan Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larson, Jeffrey; Munson, Todd; Sokolov, Vadim

2016-10-10

Platooning vehicles—connected and automated vehicles traveling with small intervehicle distances—use less fuel because of reduced aerodynamic drag. Given a network de- fined by vertex and edge sets and a set of vehicles with origin/destination nodes/times, we model and solve the combinatorial optimization problem of coordinated routing of vehicles in a manner that routes them to their destination on time while using the least amount of fuel. Common approaches decompose the platoon coordination and vehicle routing into separate problems. Our model addresses both problems simultaneously to obtain the best solution. We use modern modeling techniques and constraints implied from analyzing themore » platoon routing problem to address larger numbers of vehicles and larger networks than previously considered. While the numerical method used is unable to certify optimality for candidate solutions to all networks and parameters considered, we obtain excellent solutions in approximately one minute for much larger networks and vehicle sets than previously considered in the literature.« less

A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

PubMed Central

Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

2015-01-01

It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

Simulated annealing with restart strategy for the blood pickup routing problem

NASA Astrophysics Data System (ADS)

Yu, V. F.; Iswari, T.; Normasari, N. M. E.; Asih, A. M. S.; Ting, H.

2018-04-01

This study develops a simulated annealing heuristic with restart strategy (SA_RS) for solving the blood pickup routing problem (BPRP). BPRP minimizes the total length of the routes for blood bag collection between a blood bank and a set of donation sites, each associated with a time window constraint that must be observed. The proposed SA_RS is implemented in C++ and tested on benchmark instances of the vehicle routing problem with time windows to verify its performance. The algorithm is then tested on some newly generated BPRP instances and the results are compared with those obtained by CPLEX. Experimental results show that the proposed SA_RS heuristic effectively solves BPRP.

Solving Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) using BRKGA with local search

NASA Astrophysics Data System (ADS)

Prasetyo, H.; Alfatsani, M. A.; Fauza, G.

2018-05-01

The main issue in vehicle routing problem (VRP) is finding the shortest route of product distribution from the depot to outlets to minimize total cost of distribution. Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) is one of the variants of VRP that accommodates vehicle capacity and distribution period. Since the main problem of CCVRPTW is considered a non-polynomial hard (NP-hard) problem, it requires an efficient and effective algorithm to solve the problem. This study was aimed to develop Biased Random Key Genetic Algorithm (BRKGA) that is combined with local search to solve the problem of CCVRPTW. The algorithm design was then coded by MATLAB. Using numerical test, optimum algorithm parameters were set and compared with the heuristic method and Standard BRKGA to solve a case study on soft drink distribution. Results showed that BRKGA combined with local search resulted in lower total distribution cost compared with the heuristic method. Moreover, the developed algorithm was found to be successful in increasing the performance of Standard BRKGA.

Genetic Algorithm and Tabu Search for Vehicle Routing Problems with Stochastic Demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ismail, Zuhaimy, E-mail: zuhaimyi@yahoo.com, E-mail: irhamahn@yahoo.com; Irhamah, E-mail: zuhaimyi@yahoo.com, E-mail: irhamahn@yahoo.com

2010-11-11

This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that aremore » its robustness and better solution qualities.« less

Rapid Airlift Planning for Amphibious-Ready Groups

DTIC Science & Technology

2015-09-01

SUBJECT TERMS vehicle routing problem , vehicle synchronization, military airlift, passenger and cargo transport, helicopter routing 15. NUMBER OF PAGES...Southern California VBA Visual Basic for Applications VRP Vehicle Routing Problem xiv THIS PAGE INTENTIONALLY LEFT BLANK xv EXECUTIVE...Depending on the ICAO+ to ICAO+ distance-over-the-water (DOW), aircraft may require section support. DOW is the great- circle distance travelled

Neurally and Ocularly Informed Graph-Based Models for Searching 3D Environments

DTIC Science & Technology

2014-06-03

hBCI = hybrid brain–computer interface, TAG = transductive annotation by graph, CV = computer vision, TSP = traveling salesman problem . are navigated...environment that are most likely to contain objects that the subject would like to visit. 2.9. Route planning A traveling salesman problem (TSP) solver...fixations in a visual search task using fixation-related potentials J. Vis. 13 Croes G 1958 A method for solving traveling - salesman problems Oper. Res

Energy Efficient Probabilistic Broadcasting for Mobile Ad-Hoc Network

NASA Astrophysics Data System (ADS)

Kumar, Sumit; Mehfuz, Shabana

2017-06-01

In mobile ad-hoc network (MANETs) flooding method is used for broadcasting route request (RREQ) packet from one node to another node for route discovery. This is the simplest method of broadcasting of RREQ packets but it often results in broadcast storm problem, originating collisions and congestion of packets in the network. A probabilistic broadcasting is one of the widely used broadcasting scheme for route discovery in MANETs and provides solution for broadcasting storm problem. But it does not consider limited energy of the battery of the nodes. In this paper, a new energy efficient probabilistic broadcasting (EEPB) is proposed in which probability of broadcasting RREQs is calculated with respect to remaining energy of nodes. The analysis of simulation results clearly indicate that an EEPB route discovery scheme in ad-hoc on demand distance vector (AODV) can increase the network lifetime with a decrease in the average power consumption and RREQ packet overhead. It also decreases the number of dropped packets in the network, in comparison to other EEPB schemes like energy constraint gossip (ECG), energy aware gossip (EAG), energy based gossip (EBG) and network lifetime through energy efficient broadcast gossip (NEBG).

An Efficient Framework Model for Optimizing Routing Performance in VANETs.

PubMed

Al-Kharasani, Nori M; Zulkarnain, Zuriati Ahmad; Subramaniam, Shamala; Hanapi, Zurina Mohd

2018-02-15

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).

Anomaly detection of flight routes through optimal waypoint

NASA Astrophysics Data System (ADS)

Pusadan, M. Y.; Buliali, J. L.; Ginardi, R. V. H.

2017-01-01

Deciding factor of flight, one of them is the flight route. Flight route determined by coordinate (latitude and longitude). flight routed is determined by its coordinates (latitude and longitude) as defined is waypoint. anomaly occurs, if the aircraft is flying outside the specified waypoint area. In the case of flight data, anomalies occur by identifying problems of the flight route based on data ADS-B. This study has an aim of to determine the optimal waypoints of the flight route. The proposed methods: i) Agglomerative Hierarchical Clustering (AHC) in several segments based on range area coordinates (latitude and longitude) in every waypoint; ii) The coefficient cophenetics correlation (c) to determine the correlation between the members in each cluster; iii) cubic spline interpolation as a graphic representation of the has connected between the coordinates on every waypoint; and iv). Euclidean distance to measure distances between waypoints with 2 centroid result of clustering AHC. The experiment results are value of coefficient cophenetics correlation (c): 0,691≤ c ≤ 0974, five segments the generated of the range area waypoint coordinates, and the shortest and longest distance between the centroid with waypoint are 0.46 and 2.18. Thus, concluded that the shortest distance is used as the reference coordinates of optimal waypoint, and farthest distance can be indicated potentially detected anomaly.

Cloud-based large-scale air traffic flow optimization

NASA Astrophysics Data System (ADS)

Cao, Yi

The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.

The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

ERIC Educational Resources Information Center

Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

2016-01-01

Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems

PubMed Central

Yu, Hao; Solvang, Wei Deng

2016-01-01

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment. PMID:27258293

Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Paksi, A. B. N.; Ma'ruf, A.

2016-02-01

In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.

Modified artificial bee colony for the vehicle routing problems with time windows.

PubMed

Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana

2016-01-01

The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW.

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems.

PubMed

Yu, Hao; Solvang, Wei Deng

2016-05-31

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.

Research on logistics scheduling based on PSO

NASA Astrophysics Data System (ADS)

Bao, Huifang; Zhou, Linli; Liu, Lei

2017-08-01

With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

A memetic optimization algorithm for multi-constrained multicast routing in ad hoc networks

PubMed Central

Hammad, Karim; El Bakly, Ahmed M.

2018-01-01

A mobile ad hoc network is a conventional self-configuring network where the routing optimization problem—subject to various Quality-of-Service (QoS) constraints—represents a major challenge. Unlike previously proposed solutions, in this paper, we propose a memetic algorithm (MA) employing an adaptive mutation parameter, to solve the multicast routing problem with higher search ability and computational efficiency. The proposed algorithm utilizes an updated scheme, based on statistical analysis, to estimate the best values for all MA parameters and enhance MA performance. The numerical results show that the proposed MA improved the delay and jitter of the network, while reducing computational complexity as compared to existing algorithms. PMID:29509760

A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem

NASA Technical Reports Server (NTRS)

Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad

2010-01-01

Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.

Dynamic real-time routing for evacuation response planning and execution.

DOT National Transportation Integrated Search

2011-01-01

This study addresses the problem of dynamic routing operations in the emergency response context, primarily in terms : of the routing of response vehicles and evacuees. The study focuses on identifying the paths used for routing response : vehicles a...

An adaptive large neighborhood search heuristic for Two-Echelon Vehicle Routing Problems arising in city logistics

PubMed Central

Hemmelmayr, Vera C.; Cordeau, Jean-François; Crainic, Teodor Gabriel

2012-01-01

In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP. PMID:23483764

An adaptive large neighborhood search heuristic for Two-Echelon Vehicle Routing Problems arising in city logistics.

PubMed

Hemmelmayr, Vera C; Cordeau, Jean-François; Crainic, Teodor Gabriel

2012-12-01

In this paper, we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP). The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm outperforms existing solution methods for the 2E-VRP and achieves excellent results on the LRP.

A Linear Programming Approach to Routing Control in Networks of Constrained Nonlinear Positive Systems with Concave Flow Rates

NASA Technical Reports Server (NTRS)

Arneson, Heather M.; Dousse, Nicholas; Langbort, Cedric

2014-01-01

We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment.We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its intended destination over a finite time horizon. We give sufficient conditions for the existence of a time-varying state-dependent routing strategy which ensures that the closed-loop system satisfies basic network properties of positivity, conservation and interconnection while ensuring that capacity constraints are satisfied, when possible, or adjusted if a solution cannot be found. These conditions are formulated as a linear programming problem. Instances of this linear programming problem can be solved iteratively to generate a solution to the finite horizon routing problem. Results are given for the application of this control design method to an example problem. Key words: linear programming; control of networks; positive systems; controller constraints and structure.

Developing a model-based decision support system for call-a-ride paratransit service problems.

DOT National Transportation Integrated Search

2011-02-01

Paratransit is the transportation service that supplements larger public transportation : systems by providing individualized rides without fixed routes or timetables. In 1990, : the Americans with Disabilities Act (ADA) was passed which allows passe...

Nudging socially isolated people towards well-being with the ‘Happiness Route’: design of a randomized controlled trial for the evaluation of a happiness-based intervention

PubMed Central

2013-01-01

Background The Happiness Route is an innovative intervention that uses a happiness-based approach for people with an accumulation of risk factors for low well-being: socially isolated people with health impairments and a low socioeconomic status. The goal of this intervention is to improve well-being by engaging participants in intrinsically motivated activities with methods from positive psychology. We hypothesize that the primary outcome measure, emotional, social and psychological well-being of participants of the Happiness Route, will increase in comparison to the traditional and commonly-used problem-based approach. Secondary outcome measures are health-related quality of life, psychosocial functioning and health care consumption. Methods and design Participants will be socially isolated people with health problems and a low socioeconomic status. Participants will be recruited in ten Dutch communities and candidates will be signed up by intermediaries, professionals from the health and social sector. Randomly assigned, half of the participants will follow the Happiness Route and half of the participants will follow the active, problem-focused control group ‘Customized Care’. In total, 256 participants will be included. In both conditions, participants will receive counseling sessions from trained counselors. In the control group, participants will talk about their problems and the care they get and counselors help to optimize their care. In the Happiness Route, the counselor ask questions such as “How do you want to live your life?”. The intervention helps people to find their ‘passion’, i.e., a positive goal-engaged and intrinsically motivated activity. It enables them to follow their passion through by a once-only personal happiness budget (maximal €500). We use well-validated and reliable questionnaires to measure primary and secondary outcome measures at baseline, directly after the intervention and at a nine-month follow-up. Discussion Shortcomings of earlier intervention studies in positive psychology will be tackled with this study, such as having a target group who is especially vulnerable for low well-being. The practice-based setting is especially interesting, as it can give valuable insights in how positive psychology interventions work in practice, but can also give rise to several challenges. Trial registration Dutch Trial Register, trial registration number TC=3377NTR. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3377. PMID:24053566

Location-allocation models and new solution methodologies in telecommunication networks

NASA Astrophysics Data System (ADS)

Dinu, S.; Ciucur, V.

2016-08-01

When designing a telecommunications network topology, three types of interdependent decisions are combined: location, allocation and routing, which are expressed by the following design considerations: how many interconnection devices - consolidation points/concentrators should be used and where should they be located; how to allocate terminal nodes to concentrators; how should the voice, video or data traffic be routed and what transmission links (capacitated or not) should be built into the network. Including these three components of the decision into a single model generates a problem whose complexity makes it difficult to solve. A first method to address the overall problem is the sequential one, whereby the first step deals with the location-allocation problem and based on this solution the subsequent sub-problem (routing the network traffic) shall be solved. The issue of location and allocation in a telecommunications network, called "The capacitated concentrator location- allocation - CCLA problem" is based on one of the general location models on a network in which clients/demand nodes are the terminals and facilities are the concentrators. Like in a location model, each client node has a demand traffic, which must be served, and the facilities can serve these demands within their capacity limit. In this study, the CCLA problem is modeled as a single-source capacitated location-allocation model whose optimization objective is to determine the minimum network cost consisting of fixed costs for establishing the locations of concentrators, costs for operating concentrators and costs for allocating terminals to concentrators. The problem is known as a difficult combinatorial optimization problem for which powerful algorithms are required. Our approach proposes a Fuzzy Genetic Algorithm combined with a local search procedure to calculate the optimal values of the location and allocation variables. To confirm the efficiency of the proposed algorithm with respect to the quality of solutions, significant size test problems were considered: up to 100 terminal nodes and 50 concentrators on a 100 × 100 square grid. The performance of this hybrid intelligent algorithm was evaluated by measuring the quality of its solutions with respect to the following statistics: the standard deviation and the ratio of the best solution obtained.

New optimization model for routing and spectrum assignment with nodes insecurity

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-04-01

By adopting the orthogonal frequency division multiplexing technology, elastic optical networks can provide the flexible and variable bandwidth allocation to each connection request and get higher spectrum utilization. The routing and spectrum assignment problem in elastic optical network is a well-known NP-hard problem. In addition, information security has received worldwide attention. We combine these two problems to investigate the routing and spectrum assignment problem with the guaranteed security in elastic optical network, and establish a new optimization model to minimize the maximum index of the used frequency slots, which is used to determine an optimal routing and spectrum assignment schemes. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. The heuristic algorithm is first used to sort the connection requests and then the genetic algorithm is designed to look for an optimal routing and spectrum assignment scheme. In the genetic algorithm, tailor-made crossover, mutation and local search operators are designed. Moreover, simulation experiments are conducted with three heuristic strategies, and the experimental results indicate that the effectiveness of the proposed model and algorithm framework.

Reliable Adaptive Data Aggregation Route Strategy for a Trade-off between Energy and Lifetime in WSNs

PubMed Central

Guo, Wenzhong; Hong, Wei; Zhang, Bin; Chen, Yuzhong; Xiong, Naixue

2014-01-01

Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime. PMID:25215944

Automatic Extraction of Destinations, Origins and Route Parts from Human Generated Route Directions

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Mitra, Prasenjit; Klippel, Alexander; Maceachren, Alan

Researchers from the cognitive and spatial sciences are studying text descriptions of movement patterns in order to examine how humans communicate and understand spatial information. In particular, route directions offer a rich source of information on how cognitive systems conceptualize movement patterns by segmenting them into meaningful parts. Route directions are composed using a plethora of cognitive spatial organization principles: changing levels of granularity, hierarchical organization, incorporation of cognitively and perceptually salient elements, and so forth. Identifying such information in text documents automatically is crucial for enabling machine-understanding of human spatial language. The benefits are: a) creating opportunities for large-scale studies of human linguistic behavior; b) extracting and georeferencing salient entities (landmarks) that are used by human route direction providers; c) developing methods to translate route directions to sketches and maps; and d) enabling queries on large corpora of crawled/analyzed movement data. In this paper, we introduce our approach and implementations that bring us closer to the goal of automatically processing linguistic route directions. We report on research directed at one part of the larger problem, that is, extracting the three most critical parts of route directions and movement patterns in general: origin, destination, and route parts. We use machine-learning based algorithms to extract these parts of routes, including, for example, destination names and types. We prove the effectiveness of our approach in several experiments using hand-tagged corpora.

CCS-DTN: clustering and network coding-based efficient routing in social DTNs.

PubMed

Zhang, Zhenjing; Ma, Maode; Jin, Zhigang

2014-12-25

With the development of mobile Internet, wireless communication via mobile devices has become a hot research topic, which is typically in the form of Delay Tolerant Networks (DTNs). One critical issue in the development of DTNs is routing. Although there is a lot research work addressing routing issues in DTNs, they cannot produce an advanced solution to the comprehensive challenges since only one or two aspects (nodes' movements, clustering, centricity and so on) are considered when the routing problem is handled. In view of these defects in the existing works, we propose a novel solution to address the routing issue in social DTNs. By this solution, mobile nodes are divided into different clusters. The scheme, Spray and Wait, is used for the intra-cluster communication while a new forwarding mechanism is designed for the inter-cluster version. In our solution, the characteristics of nodes and the relation between nodes are fully considered. The simulation results show that our proposed scheme can significantly improve the performance of the routing scheme in social DTNs.

CCS-DTN: Clustering and Network Coding-Based Efficient Routing in Social DTNs

PubMed Central

Zhang, Zhenjing; Ma, Maode; Jin, Zhigang

2015-01-01

With the development of mobile Internet, wireless communication via mobile devices has become a hot research topic, which is typically in the form of Delay Tolerant Networks (DTNs). One critical issue in the development of DTNs is routing. Although there is a lot research work addressing routing issues in DTNs, they cannot produce an advanced solution to the comprehensive challenges since only one or two aspects (nodes' movements, clustering, centricity and so on) are considered when the routing problem is handled. In view of these defects in the existing works, we propose a novel solution to address the routing issue in social DTNs. By this solution, mobile nodes are divided into different clusters. The scheme, Spray and Wait, is used for the intra-cluster communication while a new forwarding mechanism is designed for the inter-cluster version. In our solution, the characteristics of nodes and the relation between nodes are fully considered. The simulation results show that our proposed scheme can significantly improve the performance of the routing scheme in social DTNs. PMID:25609047

Proposed definition of the term en route in en route aircraft noise

NASA Technical Reports Server (NTRS)

Garbell, Maurice A.

1990-01-01

The problem of en route aircraft noise was examined in a formal, dedicated, setting. Whereas the general meaning of the term en route might be intuitively understood, it is suggested that a precise formal definition of the term en route would be opportune from the outset, especially since the scientific and technical investigation of the problem of noise immissions on the ground from aircraft in flight away from the airspace of an airport may conceivably lead to administrative, regulatory, and legal consequences that would mandatorily require a precise definition of the term en route. Five flight segments, with their differing airframe configurations, engine thrusts, and airspeed management, should form the basis for the differential consideration of the noise immissions perceived on the ground underneath or near the defined segments of the flightpath in en route flight, from the end of the initial climb from an airport after takeoff until the final approach to an airport.

Bees do not use nearest-neighbour rules for optimization of multi-location routes.

PubMed

Lihoreau, Mathieu; Chittka, Lars; Le Comber, Steven C; Raine, Nigel E

2012-02-23

Animals collecting patchily distributed resources are faced with complex multi-location routing problems. Rather than comparing all possible routes, they often find reasonably short solutions by simply moving to the nearest unvisited resources when foraging. Here, we report the travel optimization performance of bumble-bees (Bombus terrestris) foraging in a flight cage containing six artificial flowers arranged such that movements between nearest-neighbour locations would lead to a long suboptimal route. After extensive training (80 foraging bouts and at least 640 flower visits), bees reduced their flight distances and prioritized shortest possible routes, while almost never following nearest-neighbour solutions. We discuss possible strategies used during the establishment of stable multi-location routes (or traplines), and how these could allow bees and other animals to solve complex routing problems through experience, without necessarily requiring a sophisticated cognitive representation of space.

MODFLOW-Based Coupled Surface Water Routing and Groundwater-Flow Simulation.

PubMed

Hughes, J D; Langevin, C D; White, J T

2015-01-01

In this paper, we present a flexible approach for simulating one- and two-dimensional routing of surface water using a numerical surface water routing (SWR) code implicitly coupled to the groundwater-flow process in MODFLOW. Surface water routing in SWR can be simulated using a diffusive-wave approximation of the Saint-Venant equations and/or a simplified level-pool approach. SWR can account for surface water flow controlled by backwater conditions caused by small water-surface gradients or surface water control structures. A number of typical surface water control structures, such as culverts, weirs, and gates, can be represented, and it is possible to implement operational rules to manage surface water stages and streamflow. The nonlinear system of surface water flow equations formulated in SWR is solved by using Newton methods and direct or iterative solvers. SWR was tested by simulating the (1) Lal axisymmetric overland flow, (2) V-catchment, and (3) modified Pinder-Sauer problems. Simulated results for these problems compare well with other published results and indicate that SWR provides accurate results for surface water-only and coupled surface water/groundwater problems. Results for an application of SWR and MODFLOW to the Snapper Creek area of Miami-Dade County, Florida, USA are also presented and demonstrate the value of coupled surface water and groundwater simulation in managed, low-relief coastal settings. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Manycast routing, modulation level and spectrum assignment over elastic optical networks

NASA Astrophysics Data System (ADS)

Luo, Xiao; Zhao, Yang; Chen, Xue; Wang, Lei; Zhang, Min; Zhang, Jie; Ji, Yuefeng; Wang, Huitao; Wang, Taili

2017-07-01

Manycast is a point to multi-point transmission framework that requires a subset of destination nodes successfully reached. It is particularly applicable for dealing with large amounts of data simultaneously in bandwidth-hungry, dynamic and cloud-based applications. As rapid increasing of traffics in these applications, the elastic optical networks (EONs) may be relied on to achieve high throughput manycast. In terms of finer spectrum granularity, the EONs could reach flexible accessing to network spectrum and efficient providing exact spectrum resource to demands. In this paper, we focus on the manycast routing, modulation level and spectrum assignment (MA-RMLSA) problem in EONs. Both EONs planning with static manycast traffic and EONs provisioning with dynamic manycast traffic are investigated. An integer linear programming (ILP) model is formulated to derive MA-RMLSA problem in static manycast scenario. Then corresponding heuristic algorithm called manycast routing, modulation level and spectrum assignment genetic algorithm (MA-RMLSA-GA) is proposed to adapt for both static and dynamic manycast scenarios. The MA-RMLSA-GA optimizes MA-RMLSA problem in destination nodes selection, routing light-tree constitution, modulation level allocation and spectrum resource assignment jointly, to achieve an effective improvement in network performance. Simulation results reveal that MA-RMLSA strategies offered by MA-RMLSA-GA have slightly disparity from the optimal solutions provided by ILP model in static scenario. Moreover, the results demonstrate that MA-RMLSA-GA realizes a highly efficient MA-RMLSA strategy with the lowest blocking probability in dynamic scenario compared with benchmark algorithms.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

On the formulation and solution of an emergency routing problem.

DOT National Transportation Integrated Search

2007-10-01

In this work, we will identify important variables that contribute to : vehicular movement in an emergency environment. In particular, we for- : mulate and pose the Convoy Routing Problem (using far fewer variables : than other important models witho...

A Sharp methodology for VLSI layout

NASA Astrophysics Data System (ADS)

Bapat, Shekhar

1993-01-01

The layout problem for VLSI circuits is recognized as a very difficult problem and has been traditionally decomposed into the several seemingly independent sub-problems of placement, global routing, and detailed routing. Although this structure achieves a reduction in programming complexity, it is also typically accompanied by a reduction in solution quality. Most current placement research recognizes that the separation is artificial, and that the placement and routing problems should be solved ideally in tandem. We propose a new interconnection model, Sharp and an associated partitioning algorithm. The Sharp interconnection model uses a partitioning shape that roughly resembles the musical sharp 'number sign' and makes extensive use of pre-computed rectilinear Steiner trees. The model is designed to generate strategic routing information along with the partitioning results. Additionally, the Sharp model also generates estimates of the routing congestion. We also propose the Sharp layout heuristic that solves the layout problem in its entirety. The Sharp layout heuristic makes extensive use of the Sharp partitioning model. The use of precomputed Steiner tree forms enables the method to model accurately net characteristics. For example, the Steiner tree forms can model both the length of the net and more importantly its route. In fact, the tree forms are also appropriate for modeling the timing delays of nets. The Sharp heuristic works to minimize both the total layout area by minimizing total net length (thus reducing the total wiring area), and the congestion imbalances in the various channels (thus reducing the unused or wasted channel area). Our heuristic uses circuit element movements amongst the different partitioning blocks and selection of alternate minimal Steiner tree forms to achieve this goal. The objective function for the algorithm can be modified readily to include other important circuit constraints like propagation delays. The layout technique first computes a very high-level approximation of the layout solution (i.e., the positions of the circuit elements and the associated net routes). The approximate solution is alternately refined, objective function. The technique creates well defined sub-problems and offers intermediary steps that can be solved in parallel, as well as a parallel mechanism to merge the sub-problem solutions.

Time Dependent Heterogeneous Vehicle Routing Problem for Catering Service Delivery Problem

NASA Astrophysics Data System (ADS)

Azis, Zainal; Mawengkang, Herman

2017-09-01

The heterogeneous vehicle routing problem (HVRP) is a variant of vehicle routing problem (VRP) which describes various types of vehicles with different capacity to serve a set of customers with known geographical locations. This paper considers the optimal service deliveries of meals of a catering company located in Medan City, Indonesia. Due to the road condition as well as traffic, it is necessary for the company to use different type of vehicle to fulfill customers demand in time. The HVRP incorporates time dependency of travel times on the particular time of the day. The objective is to minimize the sum of the costs of travelling and elapsed time over the planning horizon. The problem can be modeled as a linear mixed integer program and we address a feasible neighbourhood search approach to solve the problem.

Energy efficient motion control of the electric bus on route

NASA Astrophysics Data System (ADS)

Kotiev, G. O.; Butarovich, D. O.; Kositsyn, B. B.

2018-02-01

At present, the urgent problem is the reduction of energy costs of urban motor transport. The article proposes a method of solving this problem by developing an energy-efficient law governing the movement of an electric bus along a city route. To solve this problem, an algorithm is developed based on the dynamic programming method. The proposed method allows you to take into account the constraints imposed on the phase coordinates, control action, as well as on the time of the route. In the course of solving the problem, the model of rectilinear motion of an electric bus on a horizontal reference surface is considered, taking into account the assumptions that allow it to be adapted for the implementation of the method. For the formation of a control action in the equations of motion dynamics, an algorithm for changing the traction / braking torque on the wheels of an electric bus is considered, depending on the magnitude of the control parameter and the speed of motion. An optimal phase trajectory was obtained on a selected section of the road for the prototype of an electric bus. The article presents the comparison of simulation results obtained with the optimal energy efficient control law with the results obtained by a test driver. The comparison proved feasibility of the energy efficient control law for the automobile city electric transport.

Simulation Model for Scenario Optimization of the Ready-Mix Concrete Delivery Problem

NASA Astrophysics Data System (ADS)

Galić, Mario; Kraus, Ivan

2016-12-01

This paper introduces a discrete simulation model for solving routing and network material flow problems in construction projects. Before the description of the model a detailed literature review is provided. The model is verified using a case study of solving the ready-mix concrete network flow and routing problem in metropolitan area in Croatia. Within this study real-time input parameters were taken into account. Simulation model is structured in Enterprise Dynamics simulation software and Microsoft Excel linked with Google Maps. The model is dynamic, easily managed and adjustable, but also provides good estimation for minimization of costs and realization time in solving discrete routing and material network flow problems.

What Is the Best Route? Route-Finding Strategies of Middle School Students Using GIS

ERIC Educational Resources Information Center

Wigglesivorth, John C.

2003-01-01

This paper summarizes a research project conducted to investigate the strategies developed by middle school students to solve a route-finding problem using Arc View GIS software. Three different types of route-finding strategies were identified. Some students were visual route-finders and used a highly visual strategy; others were logical route…

Vehicle routing for the eco-efficient collection of household plastic waste.

PubMed

Bing, Xiaoyun; de Keizer, Marlies; Bloemhof-Ruwaard, Jacqueline M; van der Vorst, Jack G A J

2014-04-01

Plastic waste is a special category of municipal solid waste. Plastic waste collection is featured with various alternatives of collection methods (curbside/drop-off) and separation methods (source-/post-separation). In the Netherlands, the collection routes of plastic waste are the same as those of other waste, although plastic is different than other waste in terms of volume to weight ratio. This paper aims for redesigning the collection routes and compares the collection options of plastic waste using eco-efficiency as performance indicator. Eco-efficiency concerns the trade-off between environmental impacts, social issues and costs. The collection problem is modeled as a vehicle routing problem. A tabu search heuristic is used to improve the routes. Collection alternatives are compared by a scenario study approach. Real distances between locations are calculated with MapPoint. The scenario study is conducted based on real case data of the Dutch municipality Wageningen. Scenarios are designed according to the collection alternatives with different assumptions in collection method, vehicle type, collection frequency and collection points, etc. Results show that the current collection routes can be improved in terms of eco-efficiency performance by using our method. The source-separation drop-off collection scenario has the best performance for plastic collection assuming householders take the waste to the drop-off points in a sustainable manner. The model also shows to be an efficient decision support tool to investigate the impacts of future changes such as alternative vehicle type and different response rates. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Intelligent emission-sensitive routing for plugin hybrid electric vehicles.

PubMed

Sun, Zhonghao; Zhou, Xingshe

2016-01-01

The existing transportation sector creates heavily environmental impacts and is a prime cause for the current climate change. The need to reduce emissions from this sector has stimulated efforts to speed up the application of electric vehicles (EVs). A subset of EVs, called plug-in hybrid electric vehicles (PHEVs), backup batteries with combustion engine, which makes PHEVs have a comparable driving range to conventional vehicles. However, this hybridization comes at a cost of higher emissions than all-electric vehicles. This paper studies the routing problem for PHEVs to minimize emissions. The existing shortest-path based algorithms cannot be applied to solving this problem, because of the several new challenges: (1) an optimal route may contain circles caused by detour for recharging; (2) emissions of PHEVs not only depend on the driving distance, but also depend on the terrain and the state of charge (SOC) of batteries; (3) batteries can harvest energy by regenerative braking, which makes some road segments have negative energy consumption. To address these challenges, this paper proposes a green navigation algorithm (GNA) which finds the optimal strategies: where to go and where to recharge. GNA discretizes the SOC, then makes the PHEV routing problem to satisfy the principle of optimality. Finally, GNA adopts dynamic programming to solve the problem. We evaluate GNA using synthetic maps generated by the delaunay triangulation. The results show that GNA can save more than 10 % energy and reduce 10 % emissions when compared to the shortest path algorithm. We also observe that PHEVs with the battery capacity of 10-15 KWh detour most and nearly no detour when larger than 30 KWh. This observation gives some insights when developing PHEVs.

Optimal routing of coordinated aircraft to Identify moving surface contacts

DTIC Science & Technology

2017-06-01

Time TAO Tactical Action Officer TSP Traveling Salesman Problem TSPTW TSP with Time Windows UAV unmanned aerial vehicle VRP Vehicle Routing...Orienteering Problem (OP), while the ORCA TI formulation follows the structure of a time dependent Traveling Salesman Problem (TSP), or a time dependent...Fox, Kenneth R., Bezalel Gavish, and Stephen C. Graves. 1980. “An n- Constraint Formulation of the ( Time Dependent) Traveling Salesman Problem

Agent Reward Shaping for Alleviating Traffic Congestion

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian

2006-01-01

Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

SPAR: a security- and power-aware routing protocol for wireless ad hoc and sensor networks

NASA Astrophysics Data System (ADS)

Oberoi, Vikram; Chigan, Chunxiao

2005-05-01

Wireless Ad Hoc and Sensor Networks (WAHSNs) are vulnerable to extensive attacks as well as severe resource constraints. To fulfill the security needs, many security enhancements have been proposed. Like wise, from resource constraint perspective, many power aware schemes have been proposed to save the battery power. However, we observe that for the severely resource limited and extremely vulnerable WAHSNs, taking security or power (or any other resource) alone into consideration for protocol design is rather inadequate toward the truly "secure-and-useful" WAHSNs. For example, from resource constraint perspective, we identify one of the potential problems, the Security-Capable-Congestion (SCC) behavior, for the WAHSNs routing protocols where only the security are concerned. On the other hand, the design approach where only scarce resource is concerned, such as many power-aware WAHSNs protocols, leaves security unconsidered and is undesirable to many WAHSNs application scenarios. Motivated by these observations, we propose a co-design approach, where both the high security and effective resource consumption are targeted for WAHSNs protocol design. Specifically, we propose a novel routing protocol, Security- and Power- Aware Routing (SPAR) protocol based on this co-design approach. In SPAR, the routing decisions are made based on both security and power as routing criteria. The idea of the SPAR mechanism is routing protocol independent and therefore can be broadly integrated into any of the existing WAHSNs routing protocols. The simulation results show that SPAR outperforms the WAHSNs routing protocols where security or power alone is considered, significantly. This research finding demonstrates the proposed security- and resource- aware co-design approach is promising towards the truly "secure-and-useful" WAHSNs.

An Integer Programming Model For Solving Heterogeneous Vehicle Routing Problem With Hard Time Window considering Service Choice

NASA Astrophysics Data System (ADS)

Susilawati, Enny; Mawengkang, Herman; Efendi, Syahril

2018-01-01

Generally a Vehicle Routing Problem with time windows (VRPTW) can be defined as a problem to determine the optimal set of routes used by a fleet of vehicles to serve a given set of customers with service time restrictions; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we address a variant of the VRPTW in which the fleet of vehicle is heterogenic due to the different size of demand from customers. The problem, called Heterogeneous VRP (HVRP) also includes service levels. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model.

From the physics of interacting polymers to optimizing routes on the London Underground

PubMed Central

Yeung, Chi Ho; Saad, David; Wong, K. Y. Michael

2013-01-01

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise. PMID:23898198

From the physics of interacting polymers to optimizing routes on the London Underground.

PubMed

Yeung, Chi Ho; Saad, David; Wong, K Y Michael

2013-08-20

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise.

An Efficient Framework Model for Optimizing Routing Performance in VANETs

PubMed Central

Zulkarnain, Zuriati Ahmad; Subramaniam, Shamala

2018-01-01

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED). PMID:29462884

Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks

PubMed Central

Hieu, Tran Dinh; Dung, Le The; Kim, Byung-Seo

2016-01-01

A new generation of wireless sensor networks that harvest energy from environmental sources such as solar, vibration, and thermoelectric to power sensor nodes is emerging to solve the problem of energy limitation. Based on the photo-voltaic model, this research proposes a stability-aware geographic routing for reliable data transmissions in energy-harvesting wireless sensor networks (EH-WSNs) to provide a reliable routes selection method and potentially achieve an unlimited network lifetime. Specifically, the influences of link quality, represented by the estimated packet reception rate, on network performance is investigated. Simulation results show that the proposed method outperforms an energy-harvesting-aware method in terms of energy consumption, the average number of hops, and the packet delivery ratio. PMID:27187414

Channel and Switchbox Routing Using a Greedy Based Channel Algorithm with Outward Scanning Technique.

DTIC Science & Technology

1988-12-01

ol ) V. CONCLUSION AND DISCUSSION......................... ... 6 APPENDIX A. NPGS ROUTER USER GUIDE........................6 APPENDIX B. C PROGRAM...problem and shows some of the terminology. previously mentioned. that is peculiar to VISI routing. Clq C4 C4 C4 -4 C4 Clq -4- o C CCD Co -4 q 04 -4 oL ...34 l II 92-. -.-- -.-- , -.... -4--*- -*-- tC I I + 62- -- - ----- -. .t -- +* 0C ’l i II I o -- - ..... 4+ - -+- j- - --- +-+-g9! 6 Ol ... ... "II g4

Design of an advanced flight planning system

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1985-01-01

The demand for both fuel conservation and four-dimensional traffic management require that the preflight planning process be designed to account for advances in airborne flight management and weather forecasting. The steps and issues in designing such an advanced flight planning system are presented. Focus is placed on the different optimization options for generating the three-dimensional reference path. For the cruise phase, one can use predefined jet routes, direct routes based on a network of evenly spaced grid points, or a network where the grid points are existing navaid locations. Each choice has its own problem in determining an optimum solution. Finding the reference path is further complicated by choice of cruise altitude levels, use of a time-varying weather field, and requiring a fixed time-of-arrival (four-dimensional problem).

MICROBIAL SEQUESTRATION OF LEAD AND OTHER HEAVY METALS

EPA Science Inventory

Human activity resulting in heavy metal contamination is a worldwide concern. Lead is a potent neurotoxin that can cause heart problems, kidney damage, and mental retardation. Mercury causes toxicity based on its form and route of exposure. Effects range from allergic reactions t...

Running Clubs--A Combinatorial Investigation.

ERIC Educational Resources Information Center

Nissen, Phillip; Taylor, John

1991-01-01

Presented is a combinatorial problem based on the Hash House Harriers rule which states that the route of the run should not have previously been traversed by the club. Discovered is how many weeks the club can meet before the rule has to be broken. (KR)

Non-injection routes for allergen immunotherapy: focus on sublingual immunotherapy.

PubMed

Passalacqua, Giovanni; Guerra, Laura; Pasquali, Mercedes; Canonica, Giorgio Walter

2006-01-01

Allergen specific immunotherapy, together with drugs and allergen avoidance, is a cornerstone in the management of respiratory allergy. The non-injection or local routes were developed with the main goal of improving the safety and minimizing the risk of those side effects, which can accompany the injection route. The pure oral route and the bronchial route showed, in the clinical trials, only a marginal efficacy with not negligible side effects. Therefore, these routes are no longer recommended for clinical use. The nasal route proved effective and safe, but its efficacy is strictly limited to the nose. Moreover, the practical problems with administration have made the use of nasal immunotherapy progressively declining. The efficacy of the sublingual route is confirmed by numerous controlled trials, and a meta analysis (in allergic rhinitis). The safety profile, as derived from clinical trials and post marketing surveillance studies, is satisfactory, with mild gastrointestinal complaints being the more frequent side effect reported. Recent studies have also demonstrated that SLIT has a long-lasting effect and a preventive effect on the onset of new skin sensitizations, and interesting data on adherence and mechanisms of action have become recently available. Based on these experimental data, SLIT is now officially accepted as a viable alternative to the subcutaneous route in adults and children. Several points still need to be elucidated, including: mechanisms of action, optimal dosages, and indications in pediatric patients.

Enhanced ant colony optimization for inventory routing problem

NASA Astrophysics Data System (ADS)

Wong, Lily; Moin, Noor Hasnah

2015-10-01

The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle.

PubMed

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-05-17

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0-1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25-200 targets, 12-80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.

Solving a four-destination traveling salesman problem using Escherichia coli cells as biocomputers.

PubMed

Esau, Michael; Rozema, Mark; Zhang, Tuo Huang; Zeng, Dawson; Chiu, Stephanie; Kwan, Rachel; Moorhouse, Cadence; Murray, Cameron; Tseng, Nien-Tsu; Ridgway, Doug; Sauvageau, Dominic; Ellison, Michael

2014-12-19

The Traveling Salesman Problem involves finding the shortest possible route visiting all destinations on a map only once before returning to the point of origin. The present study demonstrates a strategy for solving Traveling Salesman Problems using modified E. coli cells as processors for massively parallel computing. Sequential, combinatorial DNA assembly was used to generate routes, in the form of plasmids made up of marker genes, each representing a path between destinations, and short connecting linkers, each representing a given destination. Upon growth of the population of modified E. coli, phenotypic selection was used to eliminate invalid routes, and statistical analysis was performed to successfully identify the optimal solution. The strategy was successfully employed to solve a four-destination test problem.

Dynamic Network Formation Using Ant Colony Optimization

DTIC Science & Technology

2009-03-01

backhauls, VRP with pick-up and delivery, VRP with satellite facilities, and VRP with time windows (Murata & Itai , 2005). The general vehicle...given route is only visited once. The objective of the basic problem is to minimize a total cost as follows (Murata & Itai , 2005): M m mc 1 min...Problem based on Ant Colony System. Second Internation Workshop on Freight Transportation and Logistics. Palermo, Italy. Murata, T., & Itai , R. (2005

A radio-aware routing algorithm for reliable directed diffusion in lossy wireless sensor networks.

PubMed

Kim, Yong-Pyo; Jung, Euihyun; Park, Yong-Jin

2009-01-01

In Wireless Sensor Networks (WSNs), transmission errors occur frequently due to node failure, battery discharge, contention or interference by objects. Although Directed Diffusion has been considered as a prominent data-centric routing algorithm, it has some weaknesses due to unexpected network errors. In order to address these problems, we proposed a radio-aware routing algorithm to improve the reliability of Directed Diffusion in lossy WSNs. The proposed algorithm is aware of the network status based on the radio information from MAC and PHY layers using a cross-layer design. The cross-layer design can be used to get detailed information about current status of wireless network such as a link quality or transmission errors of communication links. The radio information indicating variant network conditions and link quality was used to determine an alternative route that provides reliable data transmission under lossy WSNs. According to the simulation result, the radio-aware reliable routing algorithm showed better performance in both grid and random topologies with various error rates. The proposed solution suggested the possibility of providing a reliable transmission method for QoS requests in lossy WSNs based on the radio-awareness. The energy and mobility issues will be addressed in the future work.

The Time Window Vehicle Routing Problem Considering Closed Route

NASA Astrophysics Data System (ADS)

Irsa Syahputri, Nenna; Mawengkang, Herman

2017-12-01

The Vehicle Routing Problem (VRP) determines the optimal set of routes used by a fleet of vehicles to serve a given set of customers on a predefined graph; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we study a variant of the predefined graph: given a weighted graph G and vertices a and b, and given a set X of closed paths in G, find the minimum total travel cost of a-b path P such that no path in X is a subpath of P. Path P is allowed to repeat vertices and edges. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model

A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment.

PubMed

Li, Yanhui; Guo, Hao; Wang, Lin; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.

National Airspace System : persistent problems in FAA's new navigation system highlight need for periodic reevaluation

DOT National Transportation Integrated Search

2000-06-01

Currently, the Federal Aviation Administration (FAA) relies principally on a ground-based navigation system that uses various types of equipment to assist pilots in navigating their assigned routes and to provide them with guidance for landing their ...

OceanRoute: Vessel Mobility Data Processing and Analyzing Model Based on MapReduce

NASA Astrophysics Data System (ADS)

Liu, Chao; Liu, Yingjian; Guo, Zhongwen; Jing, Wei

2018-06-01

The network coverage is a big problem in ocean communication, and there is no low-cost solution in the short term. Based on the knowledge of Mobile Delay Tolerant Network (MDTN), the mobility of vessels can create the chances of end-to-end communication. The mobility pattern of vessel is one of the key metrics on ocean MDTN network. Because of the high cost, few experiments have focused on research of vessel mobility pattern for the moment. In this paper, we study the traces of more than 4000 fishing and freight vessels. Firstly, to solve the data noise and sparsity problem, we design two algorithms to filter the noise and complement the missing data based on the vessel's turning feature. Secondly, after studying the traces of vessels, we observe that the vessel's traces are confined by invisible boundary. Thirdly, through defining the distance between traces, we design MR-Similarity algorithm to find the mobility pattern of vessels. Finally, we realize our algorithm on cluster and evaluate the performance and accuracy. Our results can provide the guidelines on design of data routing protocols on ocean MDTN.

Optimizing integrated airport surface and terminal airspace operations under uncertainty

NASA Astrophysics Data System (ADS)

Bosson, Christabelle S.

In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is performed for the Los Angeles environment and probabilistic distributions of pertinent uncertainty sources are obtained. A sensitivity analysis is then carried out to assess the methodology performance and find optimal sampling parameters. Finally, simulations of increasing traffic density in the presence of uncertainty are conducted first for integrated arrivals and departures, then for integrated surface and air operations. To compare the optimization results and show the benefits of integrated operations, two aircraft separation methods are implemented that offer different routing options. The simulations of integrated air operations and the simulations of integrated air and surface operations demonstrate that significant traveling time savings, both total and individual surface and air times, can be obtained when more direct routes are allowed to be traveled even in the presence of uncertainty. The resulting routings induce however extra take off delay for departing flights. As a consequence, some flights cannot meet their initial assigned runway slot which engenders runway position shifting when comparing resulting runway sequences computed under both deterministic and stochastic conditions. The optimization is able to compute an optimal runway schedule that represents an optimal balance between total schedule delays and total travel times.

Enterprise Analysis of Strategic Airlift to Obtain Competitive Advantage Through Fuel Efficiency

DTIC Science & Technology

2014-09-18

Single Dimension Value Function SFC Specific Fuel Consumption TRANSCAP Transportation System Capability TSP Travelling Salesman Problem VFT...the value posed by limiting intermediate nodes and en route stops. According to Flood (1955), the Travelling Salesman Problem (TSP) was first...B. (1954). The Problem of Routing Aircraft, a Mathematical Solution. (No. P-561). RAND CORP SANTA MONICA CALIF. Flood, M. M. (1956). The Traveling

Scheduling and control strategies for the departure problem in air traffic control

NASA Astrophysics Data System (ADS)

Bolender, Michael Alan

Two problems relating to the departure problem in air traffic control automation are examined. The first problem that is addressed is the scheduling of aircraft for departure. The departure operations at a major US hub airport are analyzed, and a discrete event simulation of the departure operations is constructed. Specifically, the case where there is a single departure runway is considered. The runway is fed by two queues of aircraft. Each queue, in turn, is fed by a single taxiway. Two salient areas regarding scheduling are addressed. The first is the construction of optimal departure sequences for the aircraft that are queued. Several greedy search algorithms are designed to minimize the total time to depart a set of queued aircraft. Each algorithm has a different set of heuristic rules to resolve situations within the search space whenever two branches of the search tree with equal edge costs are encountered. These algorithms are then compared and contrasted with a genetic search algorithm in order to assess the performance of the heuristics. This is done in the context of a static departure problem where the length of the departure queue is fixed. A greedy algorithm which deepens the search whenever two branches of the search tree with non-unique costs are encountered is shown to outperform the other heuristic algorithms. This search strategy is then implemented in the discrete event simulation. A baseline performance level is established, and a sensitivity analysis is performed by implementing changes in traffic mix, routing, and miles-in-trail restrictions for comparison. It is concluded that to minimize the average time spent in the queue for different traffic conditions, a queue assignment algorithm is needed to maintain an even balance of aircraft in the queues. A necessary consideration is to base queue assignment upon traffic management restrictions such as miles-in-trail constraints. The second problem addresses the technical challenges associated with merging departure aircraft onto their filed routes in a congested airspace environment. Conflicts between departures and en route aircraft within the Center airspace are analyzed. Speed control, holding the aircraft; at an intermediate altitude, re-routing, and vectoring are posed as possible deconfliction maneuvers. A cost assessment of these merge strategies, which are based upon 4D fight management and conflict detection and resolution principles, is given. Several merge conflicts are studied and a cost for each resolution is computed. It is shown that vectoring tends to be the most expensive resolution technique. Altitude hold is simple, costs less than vectoring, but may require a long time for the aircraft to achieve separation. Re-routing is the simplest, and provides the most cost benefit since the aircraft flies a shorter distance than if it had followed its filed route. Speed control is shown to be ineffective as a means of increasing separation, but is effective for maintaining separation between aircraft. In addition, the affects of uncertainties on the cost are assessed. The analysis shows that cost is invariant with the decision time.

Waste management as an effort to improve urban area cleanliness and community income (journal review)

NASA Astrophysics Data System (ADS)

Kinantan, Bag; Rahim Matondang, A.; Hidayati, Juliza

2018-02-01

The problem of urban waste has reached a point of concern. Population and economic growth are thought to be the cause of increasing the waste generation. The major problem related to this condition is the increasing of waste production which is not balance with the increase of its management capacity. Based on the Law Number 18 of 2008 that waste management starts from the source by applying the 3R approach (Reduction, Reuse, Recycle). This regulation provides a way which expect the waste management can be better, so that, the level of waste service can be improved and load on landfills (TPA) can be reduced.The cost of garbage collection and transport are 85% of the total waste management cost, so if this is optimized, it will optimize the system as a whole. Subsequent research focuses on how to optimize the garbage collection and transport sub-systems by finding the shortest route of transportation to the landfill by developing a Vehicle Routing Problem (VRP) model. The development of an urban area leads to the preparation of the best route is no longer an optimal solution. The complexity of the waste problem is not only related to the technical matters, but also the social and economic problems of the community. So, it is necessary to develop a model of waste management which does not only pay attention to the technical aspects, but also the social and economic. Waste is expected to be no longer a burden, but can also be utilized economically to increase community income.

Adaptive routing in wireless communication networks using swarm intelligence

NASA Technical Reports Server (NTRS)

Arabshahi, P.; Gray, A.; Kassabalidis, I.; Das, A.; Narayanan, S.; Sharkawi, M. El; Marks, R. J.

2001-01-01

In this paper we focus on the network routing problem, and survey swarm intelligent approaches for its efficient solution, after a brief overview of power-aware routing schemes, which are important in the network examples outlined above.

Efficient distribution of toy products using ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Hidayat, S.; Nurpraja, C. A.

2017-12-01

CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.

A new method for solving routing and wavelength assignment problems under inaccurate routing information in optical networks with conversion capability

NASA Astrophysics Data System (ADS)

Luo, Yanting; Zhang, Yongjun; Gu, Wanyi

2009-11-01

In large dynamic networks it is extremely difficult to maintain accurate routing information on all network nodes. The existing studies have illustrated the impact of imprecise state information on the performance of dynamic routing and wavelength assignment (RWA) algorithms. An algorithm called Bypass Based Optical Routing (BBOR) proposed by Xavier Masip-Bruin et al can reduce the effects of having inaccurate routing information in networks operating under the wavelength-continuity constraint. Then they extended the BBOR mechanism (for convenience it's called EBBOR mechanism below) to be applied to the networks with sparse and limited wavelength conversion. But it only considers the characteristic of wavelength conversion in the step of computing the bypass-paths so that its performance may decline with increasing the degree of wavelength translation (this concept will be explained in the section of introduction again). We will demonstrate the issue through theoretical analysis and introduce a novel algorithm which modifies both the lightpath selection and the bypass-paths computation in comparison to EBBOR algorithm. Simulations show that the Modified EBBOR (MEBBOR) algorithm improves the blocking performance significantly in optical networks with Conversion Capability.

Optimization of Location-Routing Problem for Cold Chain Logistics Considering Carbon Footprint.

PubMed

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-06

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location-routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network.

Vehicle routing problem with time windows using natural inspired algorithms

NASA Astrophysics Data System (ADS)

Pratiwi, A. B.; Pratama, A.; Sa’diyah, I.; Suprajitno, H.

2018-03-01

Process of distribution of goods needs a strategy to make the total cost spent for operational activities minimized. But there are several constrains have to be satisfied which are the capacity of the vehicles and the service time of the customers. This Vehicle Routing Problem with Time Windows (VRPTW) gives complex constrains problem. This paper proposes natural inspired algorithms for dealing with constrains of VRPTW which involves Bat Algorithm and Cat Swarm Optimization. Bat Algorithm is being hybrid with Simulated Annealing, the worst solution of Bat Algorithm is replaced by the solution from Simulated Annealing. Algorithm which is based on behavior of cats, Cat Swarm Optimization, is improved using Crow Search Algorithm to make simplier and faster convergence. From the computational result, these algorithms give good performances in finding the minimized total distance. Higher number of population causes better computational performance. The improved Cat Swarm Optimization with Crow Search gives better performance than the hybridization of Bat Algorithm and Simulated Annealing in dealing with big data.

Heuristic algorithms for solving of the tool routing problem for CNC cutting machines

NASA Astrophysics Data System (ADS)

Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.

2015-11-01

The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.

Geostationary payload concepts for personal satellite communications

NASA Technical Reports Server (NTRS)

Benedicto, J.; Rinous, P.; Roberts, I.; Roederer, A.; Stojkovic, I.

1993-01-01

This paper reviews candidate satellite payload architectures for systems providing world-wide communication services to mobile users equipped with hand-held terminals based on large geostationary satellites. There are a number of problems related to the payload architecture, on-board routing and beamforming, and the design of the S-band Tx and L-band Rx antenna and front ends. A number of solutions are outlined, based on trade-offs with respect to the most significant performance parameters such as capacity, G/T, flexibility of routing traffic to beams and re-configuration of the spot-beam coverage, and payload mass and power. Candidate antenna and front-end configurations were studied, in particular direct radiating arrays, arrays magnified by a reflector and active focused reflectors with overlapping feed clusters for both transmit (multimax) and receive (beam synthesis). Regarding the on-board routing and beamforming sub-systems, analog techniques based on banks of SAW filters, FET or CMOS switches and cross-bar fixed and variable beamforming are compared with a hybrid analog/digital approach based on Chirp Fourier Transform (CFT) demultiplexer combined with digital beamforming or a fully digital processor implementation, also based on CFT demultiplexing.

La-CTP: Loop-Aware Routing for Energy-Harvesting Wireless Sensor Networks.

PubMed

Sun, Guodong; Shang, Xinna; Zuo, Yan

2018-02-02

In emerging energy-harvesting wireless sensor networks (EH-WSN), the sensor nodes can harvest environmental energy to drive their operation, releasing the user's burden in terms of frequent battery replacement, and even enabling perpetual sensing systems. In EH-WSN applications, usually, the node in energy-harvesting or recharging state has to stop working until it completes the energy replenishment. However, such temporary departures of recharging nodes severely impact the packet routing, and one immediate result is the routing loop problem. Controlling loops in connectivity-intermittent EH-WSN in an efficient way is a big challenge in practice, and so far, users still lack of effective and practicable routing protocols with loop handling. Based on the Collection Tree Protocol (CTP) widely used in traditional wireless sensor networks, this paper proposes a loop-aware routing protocol for real-world EH-WSNs, called La-CTP, which involves a new parent updating metric and a proactive, adaptive beaconing scheme to effectively suppress the occurrence of loops and unlock unavoidable loops, respectively. We constructed a 100-node testbed to evaluate La-CTP, and the experimental results showed its efficacy and efficiency.

A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment

PubMed Central

Guo, Hao; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment. PMID:24489489

Re-Purposing Google Maps Visualisation for Teaching Logistics Systems

ERIC Educational Resources Information Center

Cheong, France; Cheong, Christopher; Jie, Ferry

2012-01-01

Routing is the process of selecting appropriate paths and ordering waypoints in a network. It plays an important part in logistics and supply chain management as choosing the optimal route can minimise distribution costs. Routing optimisation, however, is a difficult problem to solve and computer software is often used to determine the best route.…

Peninsula transportation district commission route deviation feasibility study.

DOT National Transportation Integrated Search

1998-11-01

Many urban transit providers are faced with the problem of declining ridership on traditional fixed route services in low density suburban areas. As a result, many fixed route services in such areas are not economically viable for the transit provide...

A new routing enhancement scheme based on node blocking state advertisement in wavelength-routed WDM networks

NASA Astrophysics Data System (ADS)

Hu, Peigang; Jin, Yaohui; Zhang, Chunlei; He, Hao; Hu, WeiSheng

2005-02-01

The increasing switching capacity brings the optical node with considerable complexity. Due to the limitation in cost and technology, an optical node is often designed with partial switching capability and partial resource sharing. It means that the node is of blocking to some extent, for example multi-granularity switching node, which in fact is a structure using pass wavelength to reduce the dimension of OXC, and partial sharing wavelength converter (WC) OXC. It is conceivable that these blocking nodes will have great effects on the problem of routing and wavelength assignment. Some previous works studied the blocking case, partial WC OXC, using complicated wavelength assignment algorithm. But the complexities of these schemes decide them to be not in practice in real networks. In this paper, we propose a new scheme based on the node blocking state advertisement to reduce the retry or rerouting probability and improve the efficiency of routing in the networks with blocking nodes. In the scheme, node blocking state are advertised to the other nodes in networks, which will be used for subsequent route calculation to find a path with lowest blocking probability. The performance of the scheme is evaluated using discrete event model in 14-node NSFNET, all the nodes of which employ a kind of partial sharing WC OXC structure. In the simulation, a simple First-Fit wavelength assignment algorithm is used. The simulation results demonstrate that the new scheme considerably reduces the retry or rerouting probability in routing process.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

PubMed Central

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-01-01

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable. PMID:28513552

Robust and Cost-Efficient Communication Based on SNMP in Mobile Networks

NASA Astrophysics Data System (ADS)

Ryu, Sang-Hoon; Baik, Doo-Kwon

A main challenge in the design of this mobile network is the development of dynamic routing protocols that can efficiently find routes between two communicating nodes. Multimedia streaming services are receiving considerable interest in the mobile network business. An entire mobile network may change its point of attachment to the Internet. The mobile network is operated by a basic specification to support network mobility called Network Mobility (NEMO) Basic Support. However, NEMO basic Support mechanism has some problem in continuous communication. In this paper, we propose robust and cost-efficient algorithm. And we simulate proposed method and conclude some remarks.

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

Comparing genetic algorithm and particle swarm optimization for solving capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Iswari, T.; Asih, A. M. S.

2018-04-01

In the logistics system, transportation plays an important role to connect every element in the supply chain, but it can produces the greatest cost. Therefore, it is important to make the transportation costs as minimum as possible. Reducing the transportation cost can be done in several ways. One of the ways to minimizing the transportation cost is by optimizing the routing of its vehicles. It refers to Vehicle Routing Problem (VRP). The most common type of VRP is Capacitated Vehicle Routing Problem (CVRP). In CVRP, the vehicles have their own capacity and the total demands from the customer should not exceed the capacity of the vehicle. CVRP belongs to the class of NP-hard problems. These NP-hard problems make it more complex to solve such that exact algorithms become highly time-consuming with the increases in problem sizes. Thus, for large-scale problem instances, as typically found in industrial applications, finding an optimal solution is not practicable. Therefore, this paper uses two kinds of metaheuristics approach to solving CVRP. Those are Genetic Algorithm and Particle Swarm Optimization. This paper compares the results of both algorithms and see the performance of each algorithm. The results show that both algorithms perform well in solving CVRP but still needs to be improved. From algorithm testing and numerical example, Genetic Algorithm yields a better solution than Particle Swarm Optimization in total distance travelled.

Solving a bi-objective mathematical model for location-routing problem with time windows in multi-echelon reverse logistics using metaheuristic procedure

NASA Astrophysics Data System (ADS)

Ghezavati, V. R.; Beigi, M.

2016-12-01

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among established facilities and existing demand points. In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management. Our proposed RL network consists of hybrid collection/inspection centers, recovery centers and disposal centers. Here, we present a new bi-objective mathematical programming (BOMP) for LRPTW in reverse logistic. Since this type of problem is NP-hard, the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to obtain the Pareto frontier for the given problem. Several numerical examples are presented to illustrate the effectiveness of the proposed model and algorithm. Also, the present work is an effort to effectively implement the ɛ-constraint method in GAMS software for producing the Pareto-optimal solutions in a BOMP. The results of the proposed algorithm have been compared with the ɛ-constraint method. The computational results show that the ɛ-constraint method is able to solve small-size instances to optimality within reasonable computing times, and for medium-to-large-sized problems, the proposed NSGA-II works better than the ɛ-constraint.

Analysis of Optimal Transport Route Determination of Oil Palm Fresh Fruit Bunches from Plantation to Processing Factory

NASA Astrophysics Data System (ADS)

Tarigan, U.; Sidabutar, R. F.; Tarigan, U. P. P.; Chen, A.

2018-04-01

Manufacturers engaged in the business, producing CPO and kernels whose raw materials are oil palm fresh fruit bunches taken from their own plantation, generally face problems of transporting from plantation to factory where there is often a change of distance traveled by the truck the carrier of FFB is due to non-specific transport instructions. The research was conducted to determine the optimal transportation route in terms of distance, time and route number. The determination of this transportation route is solved using Nearest Neighbours and Clarke & Wright Savings methods. Based on the calculations performed then found in area I with method Nearest Neighbours has a distance of 200.78 Km while Clarke & Wright Savings as with a result of 214.09 Km. As for the harvest area, II obtained results with Nearest Neighbours method of 264.37 Km and Clarke & Wright Savings method with a total distance of 264.33 Km. Based on the calculation of the time to do all the activities of transporting FFB juxtaposed with the work time of the driver got the reduction of conveyance from 8 units to 5 units. There is also improvement of fuel efficiency by 0.8%.

An empirical evaluation of lightweight random walk based routing protocol in duty cycle aware wireless sensor networks.

PubMed

Mian, Adnan Noor; Fatima, Mehwish; Khan, Raees; Prakash, Ravi

2014-01-01

Energy efficiency is an important design paradigm in Wireless Sensor Networks (WSNs) and its consumption in dynamic environment is even more critical. Duty cycling of sensor nodes is used to address the energy consumption problem. However, along with advantages, duty cycle aware networks introduce some complexities like synchronization and latency. Due to their inherent characteristics, many traditional routing protocols show low performance in densely deployed WSNs with duty cycle awareness, when sensor nodes are supposed to have high mobility. In this paper we first present a three messages exchange Lightweight Random Walk Routing (LRWR) protocol and then evaluate its performance in WSNs for routing low data rate packets. Through NS-2 based simulations, we examine the LRWR protocol by comparing it with DYMO, a widely used WSN protocol, in both static and dynamic environments with varying duty cycles, assuming the standard IEEE 802.15.4 in lower layers. Results for the three metrics, that is, reliability, end-to-end delay, and energy consumption, show that LRWR protocol outperforms DYMO in scalability, mobility, and robustness, showing this protocol as a suitable choice in low duty cycle and dense WSNs.

Vervet monkeys use paths consistent with context-specific spatial movement heuristics.

PubMed

Teichroeb, Julie A

2015-10-01

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.

Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering.

PubMed

Yang, Yang; Zhang, Jun; Cai, Kai-quan

2015-01-01

Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and frequent maneuvers. In this paper, a novel T-AII approach is introduced to address the limitations by solving the problem with two steps that are intent modeling and intent inference. In the modeling step, an online trajectory clustering procedure is designed for recognizing the real-time available routes in replacing of the missed plan routes. In the inference step, we then present a probabilistic T-AII approach based on the multiple flight attributes to improve the inference performance in maneuvering scenarios. The proposed approach is validated with real radar trajectory and flight attributes data of 34 days collected from Chengdu terminal area in China. Preliminary results show the efficacy of the presented approach.

strange beta: An assistance system for indoor rock climbing route setting

NASA Astrophysics Data System (ADS)

Phillips, C.; Becker, L.; Bradley, E.

2012-03-01

This paper applies the mathematics of chaos to the task of designing indoor rock-climbing routes. Chaotic variation has been used to great advantage on music and dance, but the challenges here are quite different, beginning with the representation. We present a formalized system for transcribing rock climbing problems and then describe a variation generator that is designed to support human route-setters in designing new and interesting climbing problems. This variation generator, termed strange beta, uses chaos to introduce novelty. We validated this approach with a large blinded study in a commercial climbing gym, in cooperation with experienced climbers and expert route setters. The results show that strange beta can help a human setter produce routes that are at least as good as, and in some cases better than, those produced in the traditional manner.

Communications network design and costing model programmers manual

NASA Technical Reports Server (NTRS)

Logan, K. P.; Somes, S. S.; Clark, C. A.

1983-01-01

Otpimization algorithms and techniques used in the communications network design and costing model for least cost route and least cost network problems are examined from the programmer's point of view. All system program modules, the data structures within the model, and the files which make up the data base are described.

Building a model-based decision support system for solving vehicle routing and driver scheduling problems under hours of service regulations.

DOT National Transportation Integrated Search

2011-08-27

"In principle, hours-of-service (HOS) regulations are intended to help truck drivers ensure get adequate rest and perform safe operations. The new HOS regulations, however, may lead to substantial cost increases for regional common carriers which hav...

23 CFR 658.11 - Additions, deletions, exceptions, and restrictions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... analysis of suitability based on the criteria in § 658.9. (2) Proposals for additions that meet the... experiencing above normal accident rates and/or accident severities? Does analysis of the accident problem..., intersection geometrics and vulnerability of roadside hardware. (5) Is there a reasonable alternate route...

A network flow model for load balancing in circuit-switched multicomputers

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

Strategic Air Traffic Planning Using Eulerian Route Based Modeling and Optimization

NASA Astrophysics Data System (ADS)

Bombelli, Alessandro

Due to a soaring air travel growth in the last decades, air traffic management has become increasingly challenging. As a consequence, planning tools are being devised to help human decision-makers achieve a better management of air traffic. Planning tools are divided into two categories, strategic and tactical. Strategic planning generally addresses a larger planning domain and is performed days to hours in advance. Tactical planning is more localized and is performed hours to minutes in advance. An aggregate route model for strategic air traffic flow management is presented. It is an Eulerian model, describing the flow between cells of unidirectional point-to-point routes. Aggregate routes are created from flight trajectory data based on similarity measures. Spatial similarity is determined using the Frechet distance. The aggregate routes approximate actual well-traveled traffic patterns. By specifying the model resolution, an appropriate balance between model accuracy and model dimension can be achieved. For a particular planning horizon, during which weather is expected to restrict the flow, a procedure for designing airborne reroutes and augmenting the traffic flow model is developed. The dynamics of the traffic flow on the resulting network take the form of a discrete-time, linear time-invariant system. The traffic flow controls are ground holding, pre-departure rerouting and airborne rerouting. Strategic planning--determining how the controls should be used to modify the future traffic flow when local capacity violations are anticipated--is posed as an integer programming problem of minimizing a weighted sum of flight delays subject to control and capacity constraints. Several tests indicate the effectiveness of the modeling and strategic planning approach. In the final, most challenging, test, strategic planning is demonstrated for the six western-most Centers of the 22-Center national airspace. The planning time horizon is four hours long, and there is weather predicted that causes significant delays to the scheduled flights. Airborne reroute options are computed and added to the route model, and it is shown that the predicted delays can be significantly reduced. The test results also indicate the computational feasibility of the approach for a planning problem of this size.

Stochastic Routing and Scheduling Policies for Energy Harvesting Communication Networks

NASA Astrophysics Data System (ADS)

Calvo-Fullana, Miguel; Anton-Haro, Carles; Matamoros, Javier; Ribeiro, Alejandro

2018-07-01

In this paper, we study the joint routing-scheduling problem in energy harvesting communication networks. Our policies, which are based on stochastic subgradient methods on the dual domain, act as an energy harvesting variant of the stochastic family of backpresure algorithms. Specifically, we propose two policies: (i) the Stochastic Backpressure with Energy Harvesting (SBP-EH), in which a node's routing-scheduling decisions are determined by the difference between the Lagrange multipliers associated to their queue stability constraints and their neighbors'; and (ii) the Stochastic Soft Backpressure with Energy Harvesting (SSBP-EH), an improved algorithm where the routing-scheduling decision is of a probabilistic nature. For both policies, we show that given sustainable data and energy arrival rates, the stability of the data queues over all network nodes is guaranteed. Numerical results corroborate the stability guarantees and illustrate the minimal gap in performance that our policies offer with respect to classical ones which work with an unlimited energy supply.

Solving the vehicle routing problem by a hybrid meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Yousefikhoshbakht, Majid; Khorram, Esmaile

2012-08-01

The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.

Using real time traveler demand data to optimize commuter rail feeder systems.

DOT National Transportation Integrated Search

2012-08-01

"This report focuses on real time optimization of the Commuter Rail Circulator Route Network Design Problem (CRCNDP). The route configuration of the circulator system where to stop and the route among the stops is determined on a real-time ba...

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem

PubMed Central

Akutsah, Francis; Olusanya, Micheal O.; Adewumi, Aderemi O.

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems. PMID:29554662

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem.

PubMed

Ezugwu, Absalom E; Akutsah, Francis; Olusanya, Micheal O; Adewumi, Aderemi O

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems.

Robust Dynamic Multi-objective Vehicle Routing Optimization Method.

PubMed

Guo, Yi-Nan; Cheng, Jian; Luo, Sha; Gong, Dun-Wei

2017-03-21

For dynamic multi-objective vehicle routing problems, the waiting time of vehicle, the number of serving vehicles, the total distance of routes were normally considered as the optimization objectives. Except for above objectives, fuel consumption that leads to the environmental pollution and energy consumption was focused on in this paper. Considering the vehicles' load and the driving distance, corresponding carbon emission model was built and set as an optimization objective. Dynamic multi-objective vehicle routing problems with hard time windows and randomly appeared dynamic customers, subsequently, were modeled. In existing planning methods, when the new service demand came up, global vehicle routing optimization method was triggered to find the optimal routes for non-served customers, which was time-consuming. Therefore, robust dynamic multi-objective vehicle routing method with two-phase is proposed. Three highlights of the novel method are: (i) After finding optimal robust virtual routes for all customers by adopting multi-objective particle swarm optimization in the first phase, static vehicle routes for static customers are formed by removing all dynamic customers from robust virtual routes in next phase. (ii)The dynamically appeared customers append to be served according to their service time and the vehicles' statues. Global vehicle routing optimization is triggered only when no suitable locations can be found for dynamic customers. (iii)A metric measuring the algorithms' robustness is given. The statistical results indicated that the routes obtained by the proposed method have better stability and robustness, but may be sub-optimum. Moreover, time-consuming global vehicle routing optimization is avoided as dynamic customers appear.

LBMR: Load-Balanced Multipath Routing for Wireless Data-Intensive Transmission in Real-Time Medical Monitoring.

PubMed

Tseng, Chinyang Henry

2016-05-31

In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee's AODV mesh routing provides extensible multi-hop data transmission to extend network coverage, it originally does not, and needs to support some form of load balancing mechanism to avoid bottlenecks. To guarantee a more reliable multi-hop data transmission for life-critical medical applications, we have developed a multipath solution, called Load-Balanced Multipath Routing (LBMR) to replace Zigbee's routing mechanism. LBMR consists of three main parts: Layer Routing Construction (LRC), a Load Estimation Algorithm (LEA), and a Route Maintenance (RM) mechanism. LRC assigns nodes into different layers based on the node's distance to the medical data gateway. Nodes can have multiple next-hops delivering medical data toward the gateway. All neighboring layer-nodes exchange flow information containing current load, which is the used by the LEA to estimate future load of next-hops to the gateway. With LBMR, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balancing and avoid bottlenecks. Furthermore, RM can detect route failures in real-time and perform route redirection to ensure routing robustness. Since LRC and LEA prevent bottlenecks while RM ensures routing fault tolerance, LBMR provides a highly reliable routing service for medical monitoring. To evaluate these accomplishments, we compare LBMR with Zigbee's AODV and another multipath protocol, AOMDV. The simulation results demonstrate LBMR achieves better load balancing, less unreachable nodes, and better packet delivery ratio than either AODV or AOMDV.

LBMR: Load-Balanced Multipath Routing for Wireless Data-Intensive Transmission in Real-Time Medical Monitoring

PubMed Central

Tseng, Chinyang Henry

2016-01-01

In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee’s AODV mesh routing provides extensible multi-hop data transmission to extend network coverage, it originally does not, and needs to support some form of load balancing mechanism to avoid bottlenecks. To guarantee a more reliable multi-hop data transmission for life-critical medical applications, we have developed a multipath solution, called Load-Balanced Multipath Routing (LBMR) to replace Zigbee’s routing mechanism. LBMR consists of three main parts: Layer Routing Construction (LRC), a Load Estimation Algorithm (LEA), and a Route Maintenance (RM) mechanism. LRC assigns nodes into different layers based on the node’s distance to the medical data gateway. Nodes can have multiple next-hops delivering medical data toward the gateway. All neighboring layer-nodes exchange flow information containing current load, which is the used by the LEA to estimate future load of next-hops to the gateway. With LBMR, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balancing and avoid bottlenecks. Furthermore, RM can detect route failures in real-time and perform route redirection to ensure routing robustness. Since LRC and LEA prevent bottlenecks while RM ensures routing fault tolerance, LBMR provides a highly reliable routing service for medical monitoring. To evaluate these accomplishments, we compare LBMR with Zigbee’s AODV and another multipath protocol, AOMDV. The simulation results demonstrate LBMR achieves better load balancing, less unreachable nodes, and better packet delivery ratio than either AODV or AOMDV. PMID:27258297

On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

DOE PAGES

Lin, Yunyue; Wu, Qishi; Cai, Xiaoshan; ...

2010-01-01

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In themore » multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.« less

A set-covering formulation for a drayage problem with single and double container loads

NASA Astrophysics Data System (ADS)

Ghezelsoflu, A.; Di Francesco, M.; Frangioni, A.; Zuddas, P.

2018-01-01

This paper addresses a drayage problem, which is motivated by the case study of a real carrier. Its trucks carry one or two containers from a port to importers and from exporters to the port. Since up to four customers can be served in each route, we propose a set-covering formulation for this problem where all possible routes are enumerated. This model can be efficiently solved to optimality by a commercial solver, significantly outperforming a previously proposed node-arc formulation. Moreover, the model can be effectively used to evaluate a new distribution policy, which results in an enlarged set of feasible routes and can increase savings w.r.t. the policy currently employed by the carrier.

Path coloring on the Mesh

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabani, Y.

In the minimum path coloring problem, we are given a list of pairs of vertices of a graph. We are asked to connect each pair by a colored path. Paths of the same color must be edge disjoint. Our objective is to minimize the number of colors used. This problem was raised by Aggarwal et al and Raghavan and Upfal as a model for routing in all-optical networks. It is also related to questions in circuit routing. In this paper, we improve the O (ln N) approximation result of Kleinberg and Tardos for path coloring on the N x Nmore » mesh. We give an O(1) approximation algorithm to the number of colors needed, and a poly(ln ln N) approximation algorithm to the choice of paths and colors. To the best of our knowledge, these are the first sub-logarithmic bounds for any network other than trees, rings, or trees of rings. Our results are based on developing new techniques for randomized rounding. These techniques iteratively improve a fractional solution until it approaches integrality. They are motivated by the method used by Leighton, Maggs, and Rao for packet routing.« less

Social Milieu Oriented Routing: A New Dimension to Enhance Network Security in WSNs.

PubMed

Liu, Lianggui; Chen, Li; Jia, Huiling

2016-02-19

In large-scale wireless sensor networks (WSNs), in order to enhance network security, it is crucial for a trustor node to perform social milieu oriented routing to a target a trustee node to carry out trust evaluation. This challenging social milieu oriented routing with more than one end-to-end Quality of Trust (QoT) constraint has proved to be NP-complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this challenging problem. However, existing solutions cannot guarantee the efficiency of searching; that is, they can hardly avoid obtaining partial optimal solutions during a searching process. Quantum annealing (QA) uses delocalization and tunneling to avoid falling into local minima without sacrificing execution time. This has been proven a promising way to many optimization problems in recently published literatures. In this paper, for the first time, with the help of a novel approach, that is, configuration path-integral Monte Carlo (CPIMC) simulations, a QA-based optimal social trust path (QA_OSTP) selection algorithm is applied to the extraction of the optimal social trust path in large-scale WSNs. Extensive experiments have been conducted, and the experiment results demonstrate that QA_OSTP outperforms its heuristic opponents.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2018-03-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2017-12-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports.

PubMed

Schilde, M; Doerner, K F; Hartl, R F

2011-12-01

The problem of transporting patients or elderly people has been widely studied in literature and is usually modeled as a dial-a-ride problem (DARP). In this paper we analyze the corresponding problem arising in the daily operation of the Austrian Red Cross. This nongovernmental organization is the largest organization performing patient transportation in Austria. The aim is to design vehicle routes to serve partially dynamic transportation requests using a fixed vehicle fleet. Each request requires transportation from a patient's home location to a hospital (outbound request) or back home from the hospital (inbound request). Some of these requests are known in advance. Some requests are dynamic in the sense that they appear during the day without any prior information. Finally, some inbound requests are stochastic. More precisely, with a certain probability each outbound request causes a corresponding inbound request on the same day. Some stochastic information about these return transports is available from historical data. The purpose of this study is to investigate, whether using this information in designing the routes has a significant positive effect on the solution quality. The problem is modeled as a dynamic stochastic dial-a-ride problem with expected return transports. We propose four different modifications of metaheuristic solution approaches for this problem. In detail, we test dynamic versions of variable neighborhood search (VNS) and stochastic VNS (S-VNS) as well as modified versions of the multiple plan approach (MPA) and the multiple scenario approach (MSA). Tests are performed using 12 sets of test instances based on a real road network. Various demand scenarios are generated based on the available real data. Results show that using the stochastic information on return transports leads to average improvements of around 15%. Moreover, improvements of up to 41% can be achieved for some test instances.

A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack-From a Green Operation Perspective.

PubMed

Xia, Yangkun; Fu, Zhuo; Tsai, Sang-Bing; Wang, Jiangtao

2018-05-10

In order to promote the development of low-carbon logistics and economize logistics distribution costs, the vehicle routing problem with split deliveries by backpack is studied. With the help of the model of classical capacitated vehicle routing problem, in this study, a form of discrete split deliveries was designed in which the customer demand can be split only by backpack. A double-objective mathematical model and the corresponding adaptive tabu search (TS) algorithm were constructed for solving this problem. By embedding the adaptive penalty mechanism, and adopting the random neighborhood selection strategy and reinitialization principle, the global optimization ability of the new algorithm was enhanced. Comparisons with the results in the literature show the effectiveness of the proposed algorithm. The proposed method can save the costs of low-carbon logistics and reduce carbon emissions, which is conducive to the sustainable development of low-carbon logistics.

Unequal Education, Poverty and Low Growth--A Theoretical Framework for Rural Education of China

ERIC Educational Resources Information Center

Wu, Fangwei; Zhang, Deyuan; Zhang, Jinghua

2008-01-01

This paper constructs an intertemporal substitution educational model based on endogenous growth theory and examines the rural education, farmer income and rural economic growth problems in China. It shows that the households originally with the same economic endowment but different education endowment take different growth routes, the income…

An Integer Programming-Based Generalized Vehicle Routing Approach for Printed Circuit Board Assembly Optimization

ERIC Educational Resources Information Center

Seth, Anupam

2009-01-01

Production planning and scheduling for printed circuit, board assembly has so far defied standard operations research approaches due to the size and complexity of the underlying problems, resulting in unexploited automation flexibility. In this thesis, the increasingly popular collect-and-place machine configuration is studied and the assembly…

Travel optimization by foraging bumblebees through readjustments of traplines after discovery of new feeding locations.

PubMed

Lihoreau, Mathieu; Chittka, Lars; Raine, Nigel E

2010-12-01

Animals collecting resources that replenish over time often visit patches in predictable sequences called traplines. Despite the widespread nature of this strategy, we still know little about how spatial memory develops and guides individuals toward suitable routes. Here, we investigate whether flower visitation sequences by bumblebees Bombus terrestris simply reflect the order in which flowers were discovered or whether they result from more complex navigational strategies enabling bees to optimize their foraging routes. We analyzed bee flight movements in an array of four artificial flowers maximizing interfloral distances. Starting from a single patch, we sequentially added three new patches so that if bees visited them in the order in which they originally encountered flowers, they would follow a long (suboptimal) route. Bees' tendency to visit patches in their discovery order decreased with experience. Instead, they optimized their flight distances by rearranging flower visitation sequences. This resulted in the development of a primary route (trapline) and two or three less frequently used secondary routes. Bees consistently used these routes after overnight breaks while occasionally exploring novel possibilities. We discuss how maintaining some level of route flexibility could allow traplining animals to cope with dynamic routing problems, analogous to the well-known traveling salesman problem.

Optical RAM-enabled cache memory and optical routing for chip multiprocessors: technologies and architectures

NASA Astrophysics Data System (ADS)

Pleros, Nikos; Maniotis, Pavlos; Alexoudi, Theonitsa; Fitsios, Dimitris; Vagionas, Christos; Papaioannou, Sotiris; Vyrsokinos, K.; Kanellos, George T.

2014-03-01

The processor-memory performance gap, commonly referred to as "Memory Wall" problem, owes to the speed mismatch between processor and electronic RAM clock frequencies, forcing current Chip Multiprocessor (CMP) configurations to consume more than 50% of the chip real-estate for caching purposes. In this article, we present our recent work spanning from Si-based integrated optical RAM cell architectures up to complete optical cache memory architectures for Chip Multiprocessor configurations. Moreover, we discuss on e/o router subsystems with up to Tb/s routing capacity for cache interconnection purposes within CMP configurations, currently pursued within the FP7 PhoxTrot project.

La-CTP: Loop-Aware Routing for Energy-Harvesting Wireless Sensor Networks

PubMed Central

Sun, Guodong; Shang, Xinna; Zuo, Yan

2018-01-01

In emerging energy-harvesting wireless sensor networks (EH-WSN), the sensor nodes can harvest environmental energy to drive their operation, releasing the user’s burden in terms of frequent battery replacement, and even enabling perpetual sensing systems. In EH-WSN applications, usually, the node in energy-harvesting or recharging state has to stop working until it completes the energy replenishment. However, such temporary departures of recharging nodes severely impact the packet routing, and one immediate result is the routing loop problem. Controlling loops in connectivity-intermittent EH-WSN in an efficient way is a big challenge in practice, and so far, users still lack of effective and practicable routing protocols with loop handling. Based on the Collection Tree Protocol (CTP) widely used in traditional wireless sensor networks, this paper proposes a loop-aware routing protocol for real-world EH-WSNs, called La-CTP, which involves a new parent updating metric and a proactive, adaptive beaconing scheme to effectively suppress the occurrence of loops and unlock unavoidable loops, respectively. We constructed a 100-node testbed to evaluate La-CTP, and the experimental results showed its efficacy and efficiency. PMID:29393876

An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks.

PubMed

Wang, Hao; Wang, Shilian; Zhang, Eryang; Lu, Luxi

2018-05-17

Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in this paper. The proposed EBLE not only balances traffic loads according to the residual energy, but also optimizes data transmissions by selecting low-cost paths. Two phases are operated in the EBLE data transmission process: (1) candidate forwarding set selection phase and (2) data transmission phase. In candidate forwarding set selection phase, nodes update candidate forwarding nodes by broadcasting the position and residual energy level information. The cost value of available nodes is calculated and stored in each sensor node. Then in data transmission phase, high residual energy and relatively low-cost paths are selected based on the cost function and residual energy level information. We also introduce detailed analysis of optimal energy consumption in UWSNs. Numerical simulation results on a variety of node distributions and data load distributions prove that EBLE outperforms other routing protocols (BTM, BEAR and direct transmission) in terms of network lifetime and energy efficiency.

A Food Chain Algorithm for Capacitated Vehicle Routing Problem with Recycling in Reverse Logistics

NASA Astrophysics Data System (ADS)

Song, Qiang; Gao, Xuexia; Santos, Emmanuel T.

2015-12-01

This paper introduces the capacitated vehicle routing problem with recycling in reverse logistics, and designs a food chain algorithm for it. Some illustrative examples are selected to conduct simulation and comparison. Numerical results show that the performance of the food chain algorithm is better than the genetic algorithm, particle swarm optimization as well as quantum evolutionary algorithm.

Operations management in distribution networks within a smart city framework.

PubMed

Cerulli, Raffaele; Dameri, Renata Paola; Sciomachen, Anna

2017-02-20

This article studies a vehicle routing problem with environmental constraints that are motivated by the requirements for sustainable urban transport. The empirical research presents a fleet planning problem that takes into consideration both minimum cost vehicle routes and minimum pollution. The problem is formulated as a mixed integer linear programming model and experimentally validated using data collected from a real situation: a grocery company delivering goods ordered via e-channels to customers spread in the urban and metropolitan area of Genoa smart city. The proposed model is a variant of the vehicle routing problem tailored to include environmental issues and street limitations. Its novelty regards also the use of real data instances provided by the B2C grocery company. Managerial implications are the choice of both the routes and the number and type of vehicles. Results show that commercial distribution strategies achieve better results in term of both business and environmental performance, provided the smart mobility goals and constraints are included into the distribution model from the beginning. © The authors 2017. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Impact Assessment and Environmental Evaluation of Various Ammonia Production Processes

NASA Astrophysics Data System (ADS)

Bicer, Yusuf; Dincer, Ibrahim; Vezina, Greg; Raso, Frank

2017-05-01

In the current study, conventional resources-based ammonia generation routes are comparatively studied through a comprehensive life cycle assessment. The selected ammonia generation options range from mostly used steam methane reforming to partial oxidation of heavy oil. The chosen ammonia synthesis process is the most common commercially available Haber-Bosch process. The essential energy input for the methods are used from various conventional resources such as coal, nuclear, natural gas and heavy oil. Using the life cycle assessment methodology, the environmental impacts of selected methods are identified and quantified from cradle to gate. The life cycle assessment outcomes of the conventional resources based ammonia production routes show that nuclear electrolysis-based ammonia generation method yields the lowest global warming and climate change impacts while the coal-based electrolysis options bring higher environmental problems. The calculated greenhouse gas emission from nuclear-based electrolysis is 0.48 kg CO2 equivalent while it is 13.6 kg CO2 per kg of ammonia for coal-based electrolysis method.

Impact Assessment and Environmental Evaluation of Various Ammonia Production Processes.

PubMed

Bicer, Yusuf; Dincer, Ibrahim; Vezina, Greg; Raso, Frank

2017-05-01

In the current study, conventional resources-based ammonia generation routes are comparatively studied through a comprehensive life cycle assessment. The selected ammonia generation options range from mostly used steam methane reforming to partial oxidation of heavy oil. The chosen ammonia synthesis process is the most common commercially available Haber-Bosch process. The essential energy input for the methods are used from various conventional resources such as coal, nuclear, natural gas and heavy oil. Using the life cycle assessment methodology, the environmental impacts of selected methods are identified and quantified from cradle to gate. The life cycle assessment outcomes of the conventional resources based ammonia production routes show that nuclear electrolysis-based ammonia generation method yields the lowest global warming and climate change impacts while the coal-based electrolysis options bring higher environmental problems. The calculated greenhouse gas emission from nuclear-based electrolysis is 0.48 kg CO 2 equivalent while it is 13.6 kg CO 2 per kg of ammonia for coal-based electrolysis method.

Reverse Flood Routing with the Lag-and-Route Storage Model

NASA Astrophysics Data System (ADS)

Mazi, K.; Koussis, A. D.

2010-09-01

This work presents a method for reverse routing of flood waves in open channels, which is an inverse problem of the signal identification type. Inflow determination from outflow measurements is useful in hydrologic forensics and in optimal reservoir control, but has been seldom studied. Such problems are ill posed and their solution is sensitive to small perturbations present in the data, or to any related uncertainty. Therefore the major difficulty in solving this inverse problem consists in controlling the amplification of errors that inevitably befall flow measurements, from which the inflow signal is to be determined. The lag-and-route model offers a convenient framework for reverse routing, because not only is formal deconvolution not required, but also reverse routing is through a single linear reservoir. In addition, this inversion degenerates to calculating the intermediate inflow (prior to the lag step) simply as the sum of the outflow and of its time derivative multiplied by the reservoir’s time constant. The remaining time shifting (lag) of the intermediate, reversed flow presents no complications, as pure translation causes no error amplification. Note that reverse routing with the inverted Muskingum scheme (Koussis et al., submitted to the 12th Plinius Conference) fails when that scheme is specialised to the Kalinin-Miljukov model (linear reservoirs in series). The principal functioning of the reverse routing procedure was verified first with perfect field data (outflow hydrograph generated by forward routing of a known inflow hydrograph). The field data were then seeded with random error. To smooth the oscillations caused by the imperfect (measured) outflow data, we applied a multipoint Savitzky-Golay low-pass filter. The combination of reverse routing and filtering achieved an effective recovery of the inflow signal extremely efficiently. Specifically, we compared the reverse routing results of the inverted lag-and-route model and of the inverted Kalinin-Miljukov model. The latter applies the lag-and-route model’s single-reservoir inversion scheme sequentially to its cascade of linear reservoirs, the number of which is related to the stream's hydromorphology. For this purpose, we used the example of Bruen & Dooge (2007), who back-routed flow hydrographs in a 100-km long prismatic channel using a scheme for the reverse solution of the St. Venant equations of flood wave motion. The lag-and-route reverse routing model recovered the inflow hydrograph with comparable accuracy to that of the multi-reservoir, inverted Kalinin-Miljukov model, both performing as well as the box-scheme for reverse routing with the St. Venant equations. In conclusion, the success in the regaining of the inflow signal by the devised single-reservoir reverse routing procedure, with multipoint low-pass filtering, can be attributed to its simple computational structure that endows it with remarkable robustness and exceptional efficiency.

Study of intelligent building system based on the internet of things

NASA Astrophysics Data System (ADS)

Wan, Liyong; Xu, Renbo

2017-03-01

In accordance with the problem such as isolated subsystems, weak system linkage and expansibility of the bus type buildings management system, this paper based on the modern intelligent buildings has studied some related technologies of the intelligent buildings and internet of things, and designed system architecture of the intelligent buildings based on the Internet of Things. Meanwhile, this paper has also analyzed wireless networking modes, wireless communication protocol and wireless routing protocol of the intelligent buildings based on the Internet of Things.

Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint

PubMed Central

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-01

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network. PMID:29316639

A survey on routing protocols for large-scale wireless sensor networks.

PubMed

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

PubMed Central

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed. PMID:22163808

Enhanced method of fast re-routing with load balancing in software-defined networks

NASA Astrophysics Data System (ADS)

Lemeshko, Oleksandr; Yeremenko, Oleksandra

2017-11-01

A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks.

PubMed

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-03-18

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks

PubMed Central

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-01-01

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio. PMID:29562628

Autonomous control of production networks using a pheromone approach

NASA Astrophysics Data System (ADS)

Armbruster, D.; de Beer, C.; Freitag, M.; Jagalski, T.; Ringhofer, C.

2006-04-01

The flow of parts through a production network is usually pre-planned by a central control system. Such central control fails in presence of highly fluctuating demand and/or unforeseen disturbances. To manage such dynamic networks according to low work-in-progress and short throughput times, an autonomous control approach is proposed. Autonomous control means a decentralized routing of the autonomous parts themselves. The parts’ decisions base on backward propagated information about the throughput times of finished parts for different routes. So, routes with shorter throughput times attract parts to use this route again. This process can be compared to ants leaving pheromones on their way to communicate with following ants. The paper focuses on a mathematical description of such autonomously controlled production networks. A fluid model with limited service rates in a general network topology is derived and compared to a discrete-event simulation model. Whereas the discrete-event simulation of production networks is straightforward, the formulation of the addressed scenario in terms of a fluid model is challenging. Here it is shown, how several problems in a fluid model formulation (e.g. discontinuities) can be handled mathematically. Finally, some simulation results for the pheromone-based control with both the discrete-event simulation model and the fluid model are presented for a time-dependent influx.

Distributed Multihop Clustering Approach for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Israr, Nauman; Awan, Irfan

Prolonging the life time of Wireless Sensor Networks (WSNs) has been the focus of current research. One of the issues that needs to be addressed along with prolonging the network life time is to ensure uniform energy consumption across the network in WSNs especially in case of random network deployment. Cluster based routing algorithms are believed to be the best choice for WSNs because they work on the principle of divide and conquer and also improve the network life time considerably compared to flat based routing schemes. In this paper we propose a new routing strategy based on two layers clustering which exploits the redundancy property of the network in order to minimise duplicate data transmission and also make the intercluster and intracluster communication multihop. The proposed algorithm makes use of the nodes in a network whose area coverage is covered by the neighbouring nodes. These nodes are marked as temporary cluster heads and later use these temporary cluster heads randomly for multihop intercluster communication. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing across the network and is more energy efficient compared to the enhanced version of widely used Leach algorithm.

A survey on bio inspired meta heuristic based clustering protocols for wireless sensor networks

NASA Astrophysics Data System (ADS)

Datta, A.; Nandakumar, S.

2017-11-01

Recent studies have shown that utilizing a mobile sink to harvest and carry data from a Wireless Sensor Network (WSN) can improve network operational efficiency as well as maintain uniform energy consumption by the sensor nodes in the network. Due to Sink mobility, the path between two sensor nodes continuously changes and this has a profound effect on the operational longevity of the network and a need arises for a protocol which utilizes minimal resources in maintaining routes between the mobile sink and the sensor nodes. Swarm Intelligence based techniques inspired by the foraging behavior of ants, termites and honey bees can be artificially simulated and utilized to solve real wireless network problems. The author presents a brief survey on various bio inspired swarm intelligence based protocols used in routing data in wireless sensor networks while outlining their general principle and operation.

Early Failures Benefit Subsequent Task Performance.

PubMed

Igata, Hideyoshi; Sasaki, Takuya; Ikegaya, Yuji

2016-02-17

Animals navigate using cognitive maps. However, how they adaptively exploit these maps in changing environments is not fully understood. In this study, we investigated the problem-solving behaviors of mice in a complicated maze in which multiple routes with different intersections were available (Test 1). Although all mice eventually settled on the shortest route, mice that initially exhibited more trial-and-error exploration solved the maze more rapidly. We then introduced one or two barriers that obstructed learned routes such that mice had to establish novel roundabout detours (Tests 2/3). Solutions varied among mice but were predictable based on individual early trial-and-error patterns observed in Test 1: mice that had initially explored more extensively found better solutions. Finally, when the barriers were removed (Test 4), all mice reverted to the best solution after active exploration. Thus, early active exploration helps mice to develop optimal strategies.

Planning chemical syntheses with deep neural networks and symbolic AI

NASA Astrophysics Data System (ADS)

Segler, Marwin H. S.; Preuss, Mike; Waller, Mark P.

2018-03-01

To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes.

Patterns of tooth wear associated with methamphetamine use.

PubMed

Richards, J R; Brofeldt, B T

2000-08-01

Methamphetamine (MAP) abuse is a significant worldwide problem. This prospective study was conducted to determine if MAP users had distinct patterns of tooth wear. Methamphetamine users were identified and interviewed about their duration and preferred route of MAP use. Study participants were interviewed in the emergency department of a large urban university hospital serving a geographic area with a high rate of illicit MAP production and consumption. Tooth wear was documented for each study participant and scored using a previously validated index and demographic information was obtained using a questionnaire. Forty-three MAP patients were interviewed. Preferred route of administration was injection (37%) followed by snorting (33%). Patients who preferentially snorted MAP had significantly higher tooth wear in the anterior maxillary teeth than patients who injected, smoked, or ingested MAP (P = 0.005). Patients who use MAP have distinct patterns of wear based on route of administration. This difference may be explained anatomically.

Routing and Scheduling Optimization Model of Sea Transportation

NASA Astrophysics Data System (ADS)

barus, Mika debora br; asyrafy, Habib; nababan, Esther; mawengkang, Herman

2018-01-01

This paper examines the routing and scheduling optimization model of sea transportation. One of the issues discussed is about the transportation of ships carrying crude oil (tankers) which is distributed to many islands. The consideration is the cost of transportation which consists of travel costs and the cost of layover at the port. Crude oil to be distributed consists of several types. This paper develops routing and scheduling model taking into consideration some objective functions and constraints. The formulation of the mathematical model analyzed is to minimize costs based on the total distance visited by the tanker and minimize the cost of the ports. In order for the model of the problem to be more realistic and the cost calculated to be more appropriate then added a parameter that states the multiplier factor of cost increases as the charge of crude oil is filled.

A method for joint routing, wavelength dimensioning and fault tolerance for any set of simultaneous failures on dynamic WDM optical networks

NASA Astrophysics Data System (ADS)

Jara, Nicolás; Vallejos, Reinaldo; Rubino, Gerardo

2017-11-01

The design of optical networks decomposes into different tasks, where the engineers must basically organize the way the main system's resources are used, minimizing the design and operation costs and respecting critical performance constraints. More specifically, network operators face the challenge of solving routing and wavelength dimensioning problems while aiming to simultaneously minimize the network cost and to ensure that the network performance meets the level established in the Service Level Agreement (SLA). We call this the Routing and Wavelength Dimensioning (R&WD) problem. Another important problem to be solved is how to deal with failures of links when the network is operating. When at least one link fails, a high rate of data loss may occur. To avoid it, the network must be designed in such a manner that upon one or multiple failures, the affected connections can still communicate using alternative routes, a mechanism known as Fault Tolerance (FT). When the mechanism allows to deal with an arbitrary number of faults, we speak about Multiple Fault Tolerance (MFT). The different tasks before mentioned are usually solved separately, or in some cases by pairs, leading to solutions that are not necessarily close to optimal ones. This paper proposes a novel method to simultaneously solve all of them, that is, the Routing, the Wavelength Dimensioning, and the Multiple Fault Tolerance problems. The method allows to obtain: a) all the primary routes by which each connection normally transmits its information, b) the additional routes, called secondary routes, used to keep each user connected in cases where one or more simultaneous failures occur, and c) the number of wavelengths available at each link of the network, calculated such that the blocking probability of each connection is lower than a pre-determined threshold (which is a network design parameter), despite the occurrence of simultaneous link failures. The solution obtained by the new algorithm is significantly more efficient than current methods, its implementation is notably simple and its on-line operation is very fast. In the paper, different examples illustrate the results provided by the proposed technique.

A Fuzzy Goal Programming for a Multi-Depot Distribution Problem

NASA Astrophysics Data System (ADS)

Nunkaew, Wuttinan; Phruksaphanrat, Busaba

2010-10-01

A fuzzy goal programming model for solving a Multi-Depot Distribution Problem (MDDP) is proposed in this research. This effective proposed model is applied for solving in the first step of Assignment First-Routing Second (AFRS) approach. Practically, a basic transportation model is firstly chosen to solve this kind of problem in the assignment step. After that the Vehicle Routing Problem (VRP) model is used to compute the delivery cost in the routing step. However, in the basic transportation model, only depot to customer relationship is concerned. In addition, the consideration of customer to customer relationship should also be considered since this relationship exists in the routing step. Both considerations of relationships are solved using Preemptive Fuzzy Goal Programming (P-FGP). The first fuzzy goal is set by a total transportation cost and the second fuzzy goal is set by a satisfactory level of the overall independence value. A case study is used for describing the effectiveness of the proposed model. Results from the proposed model are compared with the basic transportation model that has previously been used in this company. The proposed model can reduce the actual delivery cost in the routing step owing to the better result in the assignment step. Defining fuzzy goals by membership functions are more realistic than crisps. Furthermore, flexibility to adjust goals and an acceptable satisfactory level for decision maker can also be increased and the optimal solution can be obtained.

Bus Stops Location and Bus Route Planning Using Mean Shift Clustering and Ant Colony in West Jakarta

NASA Astrophysics Data System (ADS)

Supangat, Kenny; Eko Soelistio, Yustinus

2017-03-01

Traffic Jam has been a daily problem for people in Jakarta which is one of the busiest city in Indonesia up until now. Even though the official government has tried to reduce the impact of traffic issues by developing a new public transportation which takes up a lot of resources and time, it failed to diminish the problem. The actual concern to this problem actually lies in how people move between places in Jakarta where they always using their own vehicle like cars, and motorcycles that fill most of the street in Jakarta. Among much other public transportations that roams the street of Jakarta, Buses is believed to be an efficient transportation that can move many people at once. However, the location of the bus stop is now have moved to the middle of the main road, and its too far for the nearby residence to access to it. This paper proposes an optimal location of optimal bus stops in West Jakarta that is experimentally proven to have a maximal distance of 350 m. The optimal location is estimated by means of mean shift clustering method while the optimal routes are calculated using Ant Colony algorithm. The bus stops locations rate of error is 0.07% with overall route area of 32 km. Based on our experiments, we believe our proposed bus stop plan can be an interesting alternative to reduce traffic congestion in West Jakarta.

Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

2018-01-01

Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed KDAP always performs better for all the considered networks and traffic scenarios, as compared to the conventional routing schemes, namely, KSP, HC, and LD. The proposed KDAP achieves up to 60 % , and 10.46 % improvement in terms of spectrum utilization, and resource utilization ratio, respectively, over the conventional routing schemes.

Teacher Shortages in Urban Schools: The Role of Traditional and Alternative Certification Routes in Filling the Voids.

ERIC Educational Resources Information Center

Ng, Jennifer C.

2003-01-01

Examines the impact of teacher recruitment approaches via university-based and alternative certification programs. Asserts that traditional and alternative certification efforts are by themselves limited in their potential to address the problem of teacher shortages in urban schools. Suggests that an organizational view of schools, which looks…

Routing and wavelength assignment based on normalized resource and constraints for all-optical network

NASA Astrophysics Data System (ADS)

Joo, Seong-Soon; Nam, Hyun-Soon; Lim, Chang-Kyu

2003-08-01

With the rapid growth of the Optical Internet, high capacity pipes is finally destined to support end-to-end IP on the WDM optical network. Newly launched 2D MEMS optical switching module in the market supports that expectations of upcoming a transparent optical cross-connect in the network have encouraged the field applicable research on establishing real all-optical transparent network. To open up a customer-driven bandwidth services, design of the optical transport network becomes more challenging task in terms of optimal network resource usage. This paper presents a practical approach to finding a route and wavelength assignment for wavelength routed all-optical network, which has λ-plane OXC switches and wavelength converters, and supports that optical paths are randomly set up and released by dynamic wavelength provisioning to create bandwidth between end users with timescales on the order of seconds or milliseconds. We suggest three constraints to make the RWA problem become more practical one on deployment for wavelength routed all-optical network in network view: limitation on maximum hop of a route within bearable optical network impairments, limitation on minimum hops to travel before converting a wavelength, and limitation on calculation time to find all routes for connections requested at once. We design the NRCD (Normalized Resource and Constraints for All-Optical Network RWA Design) algorithm for the Tera OXC: network resource for a route is calculated by the number of internal switching paths established in each OXC nodes on the route, and is normalized by ratio of number of paths established and number of paths equipped in a node. We show that it fits for the RWA algorithm of the wavelength routed all-optical network through real experiments on the distributed objects platform.

Strange Beta: Chaotic Variations for Indoor Rock Climbing Route Setting

NASA Astrophysics Data System (ADS)

Phillips, Caleb; Bradley, Elizabeth

2011-04-01

In this paper we apply chaotic systems to the task of sequence variation for the purpose of aiding humans in setting indoor rock climbing routes. This work expands on prior work where similar variations were used to assist in dance choreography and music composition. We present a formalization for transcription of rock climbing problems and a variation generator that is tuned for this domain and addresses some confounding problems, including a new approach to automatic selection of initial conditions. We analyze our system with a large blinded study in a commercial climbing gym in cooperation with experienced climbers and expert route setters. Our results show that our system is capable of assisting a human setter in producing routes that are at least as good as, and in some cases better than, those produced traditionally.

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.

2016-01-01

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

Operations Research Applied to Libraries.

ERIC Educational Resources Information Center

Nussbaum, Harvey

This report discusses the seven basic types of problems found in business and industry as they apply to library institutions. These seven basic types are: (1) inventory problems, (2) allocation problems, (3) queueing problems, (4) sequencing problems, (5) routing problems, (6) replacement problems and (7) search problems. (MF)

Split delivery vehicle routing problem with time windows: a case study

NASA Astrophysics Data System (ADS)

Latiffianti, E.; Siswanto, N.; Firmandani, R. A.

2018-04-01

This paper aims to implement an extension of VRP so called split delivery vehicle routing problem (SDVRP) with time windows in a case study involving pickups and deliveries of workers from several points of origin and several destinations. Each origin represents a bus stop and the destination represents either site or office location. An integer linear programming of the SDVRP problem is presented. The solution was generated using three stages of defining the starting points, assigning busses, and solving the SDVRP with time windows using an exact method. Although the overall computational time was relatively lengthy, the results indicated that the produced solution was better than the existing routing and scheduling that the firm used. The produced solution was also capable of reducing fuel cost by 9% that was obtained from shorter total distance travelled by the shuttle buses.

Fund allocation using capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina

2014-09-01

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.

Optimal routing of IP packets to multi-homed servers

NASA Astrophysics Data System (ADS)

Swartz, K. L.

1992-08-01

Multi-homing, or direct attachment to multiple networks, offers both performance and availability benefits for important servers on busy networks. Exploiting these benefits to their fullest requires a modicum of routing knowledge in the clients. Careful policy control must also be reflected in the routing used within the network to make best use of specialized and often scarce resources. While relatively straightforward in theory, this problem becomes much more difficult to solve in a real network containing often intractable implementations from a variety of vendors. This paper presents an analysis of the problem and proposes a useful solution for a typical campus network. Application of this solution at the Stanford Linear Accelerator Center is studied and the problems and pitfalls encountered are discussed, as are the workarounds used to make the system work in the real world.

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack—From a Green Operation Perspective

PubMed Central

Fu, Zhuo; Wang, Jiangtao

2018-01-01

In order to promote the development of low-carbon logistics and economize logistics distribution costs, the vehicle routing problem with split deliveries by backpack is studied. With the help of the model of classical capacitated vehicle routing problem, in this study, a form of discrete split deliveries was designed in which the customer demand can be split only by backpack. A double-objective mathematical model and the corresponding adaptive tabu search (TS) algorithm were constructed for solving this problem. By embedding the adaptive penalty mechanism, and adopting the random neighborhood selection strategy and reinitialization principle, the global optimization ability of the new algorithm was enhanced. Comparisons with the results in the literature show the effectiveness of the proposed algorithm. The proposed method can save the costs of low-carbon logistics and reduce carbon emissions, which is conducive to the sustainable development of low-carbon logistics. PMID:29747469

Research of future network with multi-layer IP address

NASA Astrophysics Data System (ADS)

Li, Guoling; Long, Zhaohua; Wei, Ziqiang

2018-04-01

The shortage of IP addresses and the scalability of routing systems [1] are challenges for the Internet. The idea of dividing existing IP addresses between identities and locations is one of the important research directions. This paper proposed a new decimal network architecture based on IPv9 [11], and decimal network IP address from E.164 principle of traditional telecommunication network, the IP address level, which helps to achieve separation and identification and location of IP address, IP address form a multilayer network structure, routing scalability problem in remission at the same time, to solve the problem of IPv4 address depletion. On the basis of IPv9, a new decimal network architecture is proposed, and the IP address of the decimal network draws on the E.164 principle of the traditional telecommunication network, and the IP addresses are hierarchically divided, which helps to realize the identification and location separation of IP addresses, the formation of multi-layer IP address network structure, while easing the scalability of the routing system to find a way out of IPv4 address exhausted. In addition to modifying DNS [10] simply and adding the function of digital domain, a DDNS [12] is formed. At the same time, a gateway device is added, that is, IPV9 gateway. The original backbone network and user network are unchanged.

Research on vehicle routing optimization for the terminal distribution of B2C E-commerce firms

NASA Astrophysics Data System (ADS)

Zhang, Shiyun; Lu, Yapei; Li, Shasha

2018-05-01

In this paper, we established a half open multi-objective optimization model for the vehicle routing problem of B2C (business-to-customer) E-Commerce firms. To minimize the current transport distance as well as the disparity between the excepted shipments and the transport capacity in the next distribution, we applied the concept of dominated solution and Pareto solutions to the standard particle swarm optimization and proposed a MOPSO (multi-objective particle swarm optimization) algorithm to support the model. Besides, we also obtained the optimization solution of MOPSO algorithm based on data randomly generated through the system, which verified the validity of the model.

What is the optimal architecture for visual information routing?

PubMed

Wolfrum, Philipp; von der Malsburg, Christoph

2007-12-01

Analyzing the design of networks for visual information routing is an underconstrained problem due to insufficient anatomical and physiological data. We propose here optimality criteria for the design of routing networks. For a very general architecture, we derive the number of routing layers and the fanout that minimize the required neural circuitry. The optimal fanout l is independent of network size, while the number k of layers scales logarithmically (with a prefactor below 1), with the number n of visual resolution units to be routed independently. The results are found to agree with data of the primate visual system.

How Prepared Do Newly-Qualified Teachers Feel? Differences between Routes and Settings

ERIC Educational Resources Information Center

Gorard, Stephen

2017-01-01

Does it matter whether teachers are trained in schools or universities? In England, there is an ongoing change in the balance of routes to becoming a newly qualified teacher (NQT). Given this, and widely-reported problems with teacher supply, it is important to consider whether there are discernible differences between the routes in terms of their…

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; Mc Coy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Wong, Kelvin K L

2016-01-01

Unmanned aerial vehicle (UAV) has been widely used in many industries. In the medical environment, especially in some emergency situations, UAVs play an important role such as the supply of medicines and blood with speed and efficiency. In this paper, we study the problem of multi-objective blood supply by UAVs in such emergency situations. This is a complex problem that includes maintenance of the supply blood's temperature model during transportation, the UAVs' scheduling and routes' planning in case of multiple sites requesting blood, and limited carrying capacity. Most importantly, we need to study the blood's temperature change due to the external environment, the heating agent (or refrigerant) and time factor during transportation, and propose an optimal method for calculating the mixing proportion of blood and appendage in different circumstances and delivery conditions. Then, by introducing the idea of transportation appendage into the traditional Capacitated Vehicle Routing Problem (CVRP), this new problem is proposed according to the factors of distance and weight. Algorithmically, we use the combination of decomposition-based multi-objective evolutionary algorithm and local search method to perform a series of experiments on the CVRP public dataset. By comparing our technique with the traditional ones, our algorithm can obtain better optimization results and time performance.

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

Multilevel semantic analysis and problem-solving in the flight-domain

NASA Technical Reports Server (NTRS)

Chien, R. T.

1982-01-01

The use of knowledge-base architecture and planning control; mechanisms to perform an intelligent monitoring task in the flight domain is addressed. The route level, the trajectory level, and parts of the aerodynamics level are demonstrated. Hierarchical planning and monitoring conceptual levels, functional-directed mechanism rationalization, and using deep-level mechanism models for diagnoses of dependent failures are discussed.

Subaru FATS (fault tracking system)

NASA Astrophysics Data System (ADS)

Winegar, Tom W.; Noumaru, Junichi

2000-07-01

The Subaru Telescope requires a fault tracking system to record the problems and questions that staff experience during their work, and the solutions provided by technical experts to these problems and questions. The system records each fault and routes it to a pre-selected 'solution-provider' for each type of fault. The solution provider analyzes the fault and writes a solution that is routed back to the fault reporter and recorded in a 'knowledge-base' for future reference. The specifications of our fault tracking system were unique. (1) Dual language capacity -- Our staff speak both English and Japanese. Our contractors speak Japanese. (2) Heterogeneous computers -- Our computer workstations are a mixture of SPARCstations, Macintosh and Windows computers. (3) Integration with prime contractors -- Mitsubishi and Fujitsu are primary contractors in the construction of the telescope. In many cases, our 'experts' are our contractors. (4) Operator scheduling -- Our operators spend 50% of their work-month operating the telescope, the other 50% is spent working day shift at the base facility in Hilo, or day shift at the summit. We plan for 8 operators, with a frequent rotation. We need to keep all operators informed on the current status of all faults, no matter the operator's location.

Wavelength converter placement for different RWA algorithms in wavelength-routed all-optical networks

NASA Astrophysics Data System (ADS)

Chu, Xiaowen; Li, Bo; Chlamtac, Imrich

2002-07-01

Sparse wavelength conversion and appropriate routing and wavelength assignment (RWA) algorithms are the two key factors in improving the blocking performance in wavelength-routed all-optical networks. It has been shown that the optimal placement of a limited number of wavelength converters in an arbitrary mesh network is an NP complete problem. There have been various heuristic algorithms proposed in the literature, in which most of them assume that a static routing and random wavelength assignment RWA algorithm is employed. However, the existing work shows that fixed-alternate routing and dynamic routing RWA algorithms can achieve much better blocking performance. Our study in this paper further demonstrates that the wavelength converter placement and RWA algorithms are closely related in the sense that a well designed wavelength converter placement mechanism for a particular RWA algorithm might not work well with a different RWA algorithm. Therefore, the wavelength converter placement and the RWA have to be considered jointly. The objective of this paper is to investigate the wavelength converter placement problem under fixed-alternate routing algorithm and least-loaded routing algorithm. Under the fixed-alternate routing algorithm, we propose a heuristic algorithm called Minimum Blocking Probability First (MBPF) algorithm for wavelength converter placement. Under the least-loaded routing algorithm, we propose a heuristic converter placement algorithm called Weighted Maximum Segment Length (WMSL) algorithm. The objective of the converter placement algorithm is to minimize the overall blocking probability. Extensive simulation studies have been carried out over three typical mesh networks, including the 14-node NSFNET, 19-node EON and 38-node CTNET. We observe that the proposed algorithms not only outperform existing wavelength converter placement algorithms by a large margin, but they also can achieve almost the same performance comparing with full wavelength conversion under the same RWA algorithm.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

A Cost Assessment of the Dayton Public Schools Vehicle Routing Problem

DTIC Science & Technology

2009-03-01

known problems: the Traveling Salesman Problem (TSP) and the Bin Packing Problem ( BPP ) (Ralphs, 2003). The VRP has a plethora of real world...well known problems: the Traveling Salesman Problem (TSP) and the Bin Packing Problem ( BPP ) (Ralphs, 2003). The VRP has a plethora of real world

Solving the detour problem in navigation: a model of prefrontal and hippocampal interactions.

PubMed

Spiers, Hugo J; Gilbert, Sam J

2015-01-01

Adapting behavior to accommodate changes in the environment is an important function of the nervous system. A universal problem for motile animals is the discovery that a learned route is blocked and a detour is required. Given the substantial neuroscience research on spatial navigation and decision-making it is surprising that so little is known about how the brain solves the detour problem. Here we review the limited number of relevant functional neuroimaging, single unit recording and lesion studies. We find that while the prefrontal cortex (PFC) consistently responds to detours, the hippocampus does not. Recent evidence suggests the hippocampus tracks information about the future path distance to the goal. Based on this evidence we postulate a conceptual model in which: Lateral PFC provides a prediction error signal about the change in the path, frontopolar and superior PFC support the re-formulation of the route plan as a novel subgoal and the hippocampus simulates the new path. More data will be required to validate this model and understand (1) how the system processes the different options; and (2) deals with situations where a new path becomes available (i.e., shortcuts).

A heuristic for efficient data distribution management in distributed simulation

NASA Astrophysics Data System (ADS)

Gupta, Pankaj; Guha, Ratan K.

2005-05-01

In this paper, we propose an algorithm for reducing the complexity of region matching and efficient multicasting in data distribution management component of High Level Architecture (HLA) Run Time Infrastructure (RTI). The current data distribution management (DDM) techniques rely on computing the intersection between the subscription and update regions. When a subscription region and an update region of different federates overlap, RTI establishes communication between the publisher and the subscriber. It subsequently routes the updates from the publisher to the subscriber. The proposed algorithm computes the update/subscription regions matching for dynamic allocation of multicast group. It provides new multicast routines that exploit the connectivity of federation by communicating updates regarding interactions and routes information only to those federates that require them. The region-matching problem in DDM reduces to clique-covering problem using the connections graph abstraction where the federations represent the vertices and the update/subscribe relations represent the edges. We develop an abstract model based on connection graph for data distribution management. Using this abstract model, we propose a heuristic for solving the region-matching problem of DDM. We also provide complexity analysis of the proposed heuristics.

Research in Network Management Techniques for Tactical Data Communications Network.

DTIC Science & Technology

1982-09-01

the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques...contro!lers are designed to perform their limited tasks optimally. For the dynamic routing problem considered here, the local controllers are node...feedback to finding in optimum stead-o-state routing (static strategies) under non - control which can be easily implemented in real time. congested

Randomized shortest-path problems: two related models.

PubMed

Saerens, Marco; Achbany, Youssef; Fouss, François; Yen, Luh

2009-08-01

This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a source node while maintaining a fixed level of entropy spread throughout the network (the exploration). It is motivated by the following scenario. Suppose you have to route agents through a network in some optimal way, for instance, by minimizing the total travel cost-nothing particular up to now-you could use a standard shortest-path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow some continual exploration of the network, avoid congestion, or avoid complete predictability of your routing strategy. In other words, you want to introduce some randomness or unpredictability in the routing policy (i.e., the routing policy is randomized). This problem, which will be called the randomized shortest-path problem (RSP), is investigated in this work. The global level of randomness of the routing policy is quantified by the expected Shannon entropy spread throughout the network and is provided a priori by the designer. Then, necessary conditions to compute the optimal randomized policy-minimizing the expected routing cost-are derived. Iterating these necessary conditions, reminiscent of Bellman's value iteration equations, allows computing an optimal policy, that is, a set of transition probabilities in each node. Interestingly and surprisingly enough, this first model, while formulated in a totally different framework, is equivalent to Akamatsu's model ( 1996 ), appearing in transportation science, for a special choice of the entropy constraint. We therefore revisit Akamatsu's model by recasting it into a sum-over-paths statistical physics formalism allowing easy derivation of all the quantities of interest in an elegant, unified way. For instance, it is shown that the unique optimal policy can be obtained by solving a simple linear system of equations. This second model is therefore more convincing because of its computational efficiency and soundness. Finally, simulation results obtained on simple, illustrative examples show that the models behave as expected.

A new approach on auxiliary vehicle assignment in capacitated location routing problem

NASA Astrophysics Data System (ADS)

Bashiri, Mahdi; Rasoulinejad, Zeinab; Fallahzade, Ehsan

2016-03-01

The location routing problem (LRP) considers locating depots and vehicle routing decisions simultaneously. In classic LRP the number of customers in each route depends on the capacity of the vehicle. In this paper a capacitated LRP model with auxiliary vehicle assignment is presented in which the length of each route is not restricted by main vehicle capacity. Two kinds of vehicles are considered: main vehicles with higher capacity and fixed cost and auxiliary vehicles with lower capacity and fixed cost. The auxiliary vehicles can be added to the transportation system as an alternative strategy to cover the capacity limitations and they are just used to transfer goods from depots to vehicles and cannot serve the customers by themselves. To show the applicability of the proposed model, some numerical examples derived from the well-known instances are used. Moreover the model has been solved by some meta-heuristics for large sized instances. The results show the efficiency of the proposed model and the solution approach, considering the classic model and the exact solution approach, respectively.

Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2017-04-01

Capacitated Vehicle Routing Problem-Investment Fund Allocation Problem (CVRP-IFAP) provides investors with a sequence of assets to allocate their funds into. To minimize total risks of investment in CVRP-IFAP covariance values measure the risks between two assets. Another measure of risks are correlation values between returns. The correlation values can be used to diversify the risk of investment loss in order to optimize expected return against a certain level of risk. This study compares the total risk obtained from CVRP-IFAP when using covariance values and correlation values. Results show that CVRP-IFAP with covariance values provides lesser total risks and a significantly better measure of risk.

A novel approach to find and optimize bin locations and collection routes using a geographic information system.

PubMed

Erfani, Seyed Mohammad Hassan; Danesh, Shahnaz; Karrabi, Seyed Mohsen; Shad, Rouzbeh

2017-07-01

One of the major challenges in big cities is planning and implementation of an optimized, integrated solid waste management system. This optimization is crucial if environmental problems are to be prevented and the expenses to be reduced. A solid waste management system consists of many stages including collection, transfer and disposal. In this research, an integrated model was proposed and used to optimize two functional elements of municipal solid waste management (storage and collection systems) in the Ahmadabad neighbourhood located in the City of Mashhad - Iran. The integrated model was performed by modelling and solving the location allocation problem and capacitated vehicle routing problem (CVRP) through Geographic Information Systems (GIS). The results showed that the current collection system is not efficient owing to its incompatibility with the existing urban structure and population distribution. Application of the proposed model could significantly improve the storage and collection system. Based on the results of minimizing facilities analyses, scenarios with 100, 150 and 180 m walking distance were considered to find optimal bin locations for Alamdasht, C-metri and Koohsangi. The total number of daily collection tours was reduced to seven as compared to the eight tours carried out in the current system (12.50% reduction). In addition, the total number of required crews was minimized and reduced by 41.70% (24 crews in the current collection system vs 14 in the system provided by the model). The total collection vehicle routing was also optimized such that the total travelled distances during night and day working shifts was cut back by 53%.

Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports

PubMed Central

Schilde, M.; Doerner, K.F.; Hartl, R.F.

2011-01-01

The problem of transporting patients or elderly people has been widely studied in literature and is usually modeled as a dial-a-ride problem (DARP). In this paper we analyze the corresponding problem arising in the daily operation of the Austrian Red Cross. This nongovernmental organization is the largest organization performing patient transportation in Austria. The aim is to design vehicle routes to serve partially dynamic transportation requests using a fixed vehicle fleet. Each request requires transportation from a patient's home location to a hospital (outbound request) or back home from the hospital (inbound request). Some of these requests are known in advance. Some requests are dynamic in the sense that they appear during the day without any prior information. Finally, some inbound requests are stochastic. More precisely, with a certain probability each outbound request causes a corresponding inbound request on the same day. Some stochastic information about these return transports is available from historical data. The purpose of this study is to investigate, whether using this information in designing the routes has a significant positive effect on the solution quality. The problem is modeled as a dynamic stochastic dial-a-ride problem with expected return transports. We propose four different modifications of metaheuristic solution approaches for this problem. In detail, we test dynamic versions of variable neighborhood search (VNS) and stochastic VNS (S-VNS) as well as modified versions of the multiple plan approach (MPA) and the multiple scenario approach (MSA). Tests are performed using 12 sets of test instances based on a real road network. Various demand scenarios are generated based on the available real data. Results show that using the stochastic information on return transports leads to average improvements of around 15%. Moreover, improvements of up to 41% can be achieved for some test instances. PMID:23543641

FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network.

PubMed

He, Wei; Pillement, Sebastien; Xu, Du

2017-11-23

Clustering is an efficient approach in a wireless sensor network (WSN) to reduce the energy consumption of nodes and to extend the lifetime of the network. Unfortunately, this approach requires that all cluster heads (CHs) transmit their data to the base station (BS), which gives rise to the long distance communications problem, and in multi-hop routing, the CHs near the BS have to forward data from other nodes that lead those CHs to die prematurely, creating the hot zones problem. Unequal clustering has been proposed to solve these problems. Most of the current algorithms elect CH only by considering their competition radius, leading to unevenly distributed cluster heads. Furthermore, global distances values are needed when calculating the competition radius, which is a tedious task in large networks. To face these problems, we propose a flooding tree uneven clustering protocol (FTUC) suited for large networks. Based on the construction of a tree type sub-network to calculate the minimum and maximum distances values of the network, we then apply the unequal cluster theory. We also introduce referenced position circles to evenly elect cluster heads. Therefore, cluster heads are elected depending on the node's residual energy and their distance to a referenced circle. FTUC builds the best inter-cluster communications route by evaluating a cluster head cost function to find the best next hop to the BS. The simulation results show that the FTUC algorithm decreases the energy consumption of the nodes and balances the global energy consumption effectively, thus extending the lifetime of the network.

Global Optimization of Emergency Evacuation Assignments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Lee; Yuan, Fang; Chin, Shih-Miao

2006-01-01

Conventional emergency evacuation plans often assign evacuees to fixed routes or destinations based mainly on geographic proximity. Such approaches can be inefficient if the roads are congested, blocked, or otherwise dangerous because of the emergency. By not constraining evacuees to prespecified destinations, a one-destination evacuation approach provides flexibility in the optimization process. We present a framework for the simultaneous optimization of evacuation-traffic distribution and assignment. Based on the one-destination evacuation concept, we can obtain the optimal destination and route assignment by solving a one-destination traffic-assignment problem on a modified network representation. In a county-wide, large-scale evacuation case study, the one-destinationmore » model yields substantial improvement over the conventional approach, with the overall evacuation time reduced by more than 60 percent. More importantly, emergency planners can easily implement this framework by instructing evacuees to go to destinations that the one-destination optimization process selects.« less

Fabrication Routes for Continuous Fiber-Reinforced Ceramic Composites (CFCC)

NASA Technical Reports Server (NTRS)

DiCarlo, James A.; Bansal, Narottam P.

1998-01-01

The primary approaches used for fabrication of continuous fiber-reinforced ceramic composite (CFCC) components have been reviewed. The CFCC fabrication issues related to fiber, interface, and matrix have been analyzed. The capabilities, advantages and limitations of the five matrix-infiltration routes have been compared and discussed. Today, the best fabrication route for the CFCC end-user is not clear and compromises need to be made depending on the details of the CFCC application. However, with time, this problem should be reduced as research continues to develop advanced CFCC constituents and fabrication routes.

Fabrication Routes for Continuous Fiber-Reinforced Ceramic Composites (CFCC)

NASA Technical Reports Server (NTRS)

DiCarlo, James A.; Bansal, Narottam P.

1998-01-01

The primary approaches used for fabrication of continuous fiber-reinforced ceramic composite (CFCC) components have been reviewed. The CFCC fabrication issues related to fiber, interface, and matrix have been analyzed. The capabilities. advantages and limitations of the five matrix-infiltration routes have been compared and discussed. Today. the best fabrication route for the CFCC end-user is not clear and compromises need to be made depending on the details of the CFCC application. However, with time, this problem should be reduced as research continues to develop advanced CFCC constituents and fabrication routes.

Unintentional Infusion of Phenylephrine into the Epidural Space.

PubMed

Townley, Kress R; Lane, Jason; Packer, Robyn; Gupta, Rajnish K

2016-03-01

We describe a patient who received an unintentionally prolonged epidural infusion of phenylephrine. The patient experienced no major morbidity. However, this case highlights the continuing problem of wrong-route drug administration and the urgent need to adopt route-specific connections.

Routing strategies for efficient deployment of alternative fuel vehicles for freight delivery.

DOT National Transportation Integrated Search

2017-02-01

With increasing concerns on environmental issues, recent research on Vehicle Routing Problems : (VRP) has added new factors such as greenhouse gas emissions and alternative fuel vehicles into : the models. In this report, we consider one such promisi...

Efficiencies in freight & passenger routing & scheduling.

DOT National Transportation Integrated Search

2015-08-01

The problem we study concerns routing a fleet of capacitated vehicles in real time to collect : shipment orders placed by a known set of customers. On each day of operation, only a subset of : all customers request service. Some of these requests are...

Multisensor signal processing techniques (hybrid GPS Loran-C with RAIM)

DOT National Transportation Integrated Search

1991-09-01

One of the major elements in alleviating existing problems in en route airspace is : to allow more aircraft to traverse a given volume of airspace. Recent developments : in navigation systems will support this effort by enabling user preferred routes...

Key Management Scheme Based on Route Planning of Mobile Sink in Wireless Sensor Networks.

PubMed

Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming; Chen, Wei

2016-01-29

In many wireless sensor network application scenarios the key management scheme with a Mobile Sink (MS) should be fully investigated. This paper proposes a key management scheme based on dynamic clustering and optimal-routing choice of MS. The concept of Traveling Salesman Problem with Neighbor areas (TSPN) in dynamic clustering for data exchange is proposed, and the selection probability is used in MS route planning. The proposed scheme extends static key management to dynamic key management by considering the dynamic clustering and mobility of MSs, which can effectively balance the total energy consumption during the activities. Considering the different resources available to the member nodes and sink node, the session key between cluster head and MS is established by modified an ECC encryption with Diffie-Hellman key exchange (ECDH) algorithm and the session key between member node and cluster head is built with a binary symmetric polynomial. By analyzing the security of data storage, data transfer and the mechanism of dynamic key management, the proposed scheme has more advantages to help improve the resilience of the key management system of the network on the premise of satisfying higher connectivity and storage efficiency.

Performance Improvement in Geographic Routing for Vehicular Ad Hoc Networks

PubMed Central

Kaiwartya, Omprakash; Kumar, Sushil; Lobiyal, D. K.; Abdullah, Abdul Hanan; Hassan, Ahmed Nazar

2014-01-01

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed. PMID:25429415

Performance improvement in geographic routing for Vehicular Ad Hoc Networks.

PubMed

Kaiwartya, Omprakash; Kumar, Sushil; Lobiyal, D K; Abdullah, Abdul Hanan; Hassan, Ahmed Nazar

2014-11-25

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Dr. Li; Cui, Xiaohui; Cemerlic, Alma

Ad hoc networks are very helpful in situations when no fixed network infrastructure is available, such as natural disasters and military conflicts. In such a network, all wireless nodes are equal peers simultaneously serving as both senders and routers for other nodes. Therefore, how to route packets through reliable paths becomes a fundamental problems when behaviors of certain nodes deviate from wireless ad hoc routing protocols. We proposed a novel Dirichlet reputation model based on Bayesian inference theory which evaluates reliability of each node in terms of packet delivery. Our system offers a way to predict and select a reliablemore » path through combination of first-hand observation and second-hand reputation reports. We also proposed moving window mechanism which helps to adjust ours responsiveness of our system to changes of node behaviors. We integrated the Dirichlet reputation into routing protocol of wireless ad hoc networks. Our extensive simulation indicates that our proposed reputation system can improve good throughput of the network and reduce negative impacts caused by misbehaving nodes.« less

DS-ARP: a new detection scheme for ARP spoofing attacks based on routing trace for ubiquitous environments.

PubMed

Song, Min Su; Lee, Jae Dong; Jeong, Young-Sik; Jeong, Hwa-Young; Park, Jong Hyuk

2014-01-01

Despite the convenience, ubiquitous computing suffers from many threats and security risks. Security considerations in the ubiquitous network are required to create enriched and more secure ubiquitous environments. The address resolution protocol (ARP) is a protocol used to identify the IP address and the physical address of the associated network card. ARP is designed to work without problems in general environments. However, since it does not include security measures against malicious attacks, in its design, an attacker can impersonate another host using ARP spoofing or access important information. In this paper, we propose a new detection scheme for ARP spoofing attacks using a routing trace, which can be used to protect the internal network. Tracing routing can find the change of network movement path. The proposed scheme provides high constancy and compatibility because it does not alter the ARP protocol. In addition, it is simple and stable, as it does not use a complex algorithm or impose extra load on the computer system.

DS-ARP: A New Detection Scheme for ARP Spoofing Attacks Based on Routing Trace for Ubiquitous Environments

PubMed Central

Song, Min Su; Lee, Jae Dong; Jeong, Hwa-Young; Park, Jong Hyuk

2014-01-01

Despite the convenience, ubiquitous computing suffers from many threats and security risks. Security considerations in the ubiquitous network are required to create enriched and more secure ubiquitous environments. The address resolution protocol (ARP) is a protocol used to identify the IP address and the physical address of the associated network card. ARP is designed to work without problems in general environments. However, since it does not include security measures against malicious attacks, in its design, an attacker can impersonate another host using ARP spoofing or access important information. In this paper, we propose a new detection scheme for ARP spoofing attacks using a routing trace, which can be used to protect the internal network. Tracing routing can find the change of network movement path. The proposed scheme provides high constancy and compatibility because it does not alter the ARP protocol. In addition, it is simple and stable, as it does not use a complex algorithm or impose extra load on the computer system. PMID:25243205

Dynamic Routing for Delay-Tolerant Networking in Space Flight Operations

NASA Technical Reports Server (NTRS)

Burleigh, Scott

2008-01-01

Computational self-sufficiency - the making of communication decisions on the basis of locally available information that is already in place, rather than on the basis of information residing at other entities - is a fundamental principle of Delay-Tolerant Networking. Contact Graph Routing is an attempt to apply this principle to the problem of dynamic routing in an interplanetary DTN. Testing continues, but preliminary results are promising.

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

NASA Technical Reports Server (NTRS)

Balaban, Edward; Roychoudhury, Indranil; Spirkovska, Lilly; Sankararaman, Shankar; Kulkarni, Chetan; Arnon, Tomer

2017-01-01

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

On Trust Evaluation in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Nguyen, Dang Quan; Lamont, Louise; Mason, Peter C.

Trust has been considered as a social relationship between two individuals in human society. But, as computer science and networking have succeeded in using computers to automate many tasks, the concept of trust can be generalized to cover the reliability and relationships of non-human interaction, such as, for example, information gathering and data routing. This paper investigates the evaluation of trust in the context of ad hoc networks. Nodes evaluate each other’s behaviour based on observables. A node then decides whether to trust another node to have certain innate abilities. We show how accurate such an evaluation could be. We also provide the minimum number of observations required to obtain an accurate evaluation, a result that indicates that observation-based trust in ad hoc networks will remain a challenging problem. The impact of making networking decisions using trust evaluation on the network connectivity is also examined. In this manner, quantitative decisions can be made concerning trust-based routing with the knowledge of the potential impact on connectivity.

Fault Mitigation Schemes for Future Spaceflight Multicore Processors

NASA Technical Reports Server (NTRS)

Alexander, James W.; Clement, Bradley J.; Gostelow, Kim P.; Lai, John Y.

2012-01-01

Future planetary exploration missions demand significant advances in on-board computing capabilities over current avionics architectures based on a single-core processing element. The state-of-the-art multi-core processor provides much promise in meeting such challenges while introducing new fault tolerance problems when applied to space missions. Software-based schemes are being presented in this paper that can achieve system-level fault mitigation beyond that provided by radiation-hard-by-design (RHBD). For mission and time critical applications such as the Terrain Relative Navigation (TRN) for planetary or small body navigation, and landing, a range of fault tolerance methods can be adapted by the application. The software methods being investigated include Error Correction Code (ECC) for data packet routing between cores, virtual network routing, Triple Modular Redundancy (TMR), and Algorithm-Based Fault Tolerance (ABFT). A robust fault tolerance framework that provides fail-operational behavior under hard real-time constraints and graceful degradation will be demonstrated using TRN executing on a commercial Tilera(R) processor with simulated fault injections.

Distributed multiple path routing in complex networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Wang, San-Xiu; Wu, Ling-Wei; Mei, Pan; Yang, Xu-Hua; Wen, Guang-Hui

2016-12-01

Routing in complex transmission networks is an important problem that has garnered extensive research interest in the recent years. In this paper, we propose a novel routing strategy called the distributed multiple path (DMP) routing strategy. For each of the O-D node pairs in a given network, the DMP routing strategy computes and stores multiple short-length paths that overlap less with each other in advance. And during the transmission stage, it rapidly selects an actual routing path which provides low transmission cost from the pre-computed paths for each transmission task, according to the real-time network transmission status information. Computer simulation results obtained for the lattice, ER random, and scale-free networks indicate that the strategy can significantly improve the anti-congestion ability of transmission networks, as well as provide favorable routing robustness against partial network failures.

Modeling and optimization of the multiobjective stochastic joint replenishment and delivery problem under supply chain environment.

PubMed

Wang, Lin; Qu, Hui; Liu, Shan; Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted.

Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment

PubMed Central

Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted. PMID:24302880

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Design and Implementation of Secure Area Expansion Scheme for Public Wireless LAN Services

NASA Astrophysics Data System (ADS)

Watanabe, Ryu; Tanaka, Toshiaki

Recently, wireless LAN (WLAN) technology has become a major wireless communication method. The communication bandwidth is increasing and speeds have attained rates exceeding 100 Mbps. Therefore, WLAN technology is regarded as one of the promising communication methods for future networks. In addition, public WLAN connection services can be used in many locations. However, the number of the access points (AP) is insufficient for seamless communication and it cannot be said that users can use the service ubiquitously. An ad-hoc network style connection can be used to expand the coverage area of a public WLAN service. By relaying the user messages among the user nodes, a node can obtain an Internet connection via an AP, even though the node is located outside the AP's direct wireless connection area. Such a coverage area extending technology has many advantages thanks to the feature that no additional infrastructure is required. Therefore, there is a strong demand for this technology as it allows the cost-effective construction of future networks. When a secure ad-hoc routing protocol is used for message exchange in the WLAN service, the message routes are protected from malicious behavior such as route forging and can be maintained appropriately. To do this, however, a new node that wants to join the WLAN service has to obtain information such as the public key certificate and IP address in order to start secure ad-hoc routing. In other words, an initial setup is required for every network node to join the WLAN service properly. Ordinarily, such information should be assigned from the AP. However, new nodes cannot always contact an AP directly. Therefore, there are problems about information delivery in the initial setup of a network node. These problems originate in the multi hop connection based on the ad-hoc routing protocols. In order to realize an expanded area WLAN service, in this paper, the authors propose a secure public key certificate and address provision scheme during the initial setup phase on mobile nodes for the service. The proposed scheme also considers the protection of user privacy. Accordingly, none of the user nodes has to reveal their unique and persistent information to other nodes. Instead of using such information, temporary values are sent by an AP to mobile nodes and used for secure ad-hoc routing operations. Therefore, our proposed scheme prevents tracking by malicious parties by avoiding the use of unique information. Moreover, a test bed was also implemented based on the proposal and an evaluation was carried out in order to confirm performance. In addition, the authors describe a countermeasure against denial of service (DoS) attacks based on the approach to privacy protection described in our proposal.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

To the North Coast of Devon: Collaborative Navigation While Exploring Unfamiliar Terrain

NASA Technical Reports Server (NTRS)

Clancey, William J.; Lee, Pascal; Cockell, Charles S.; Braham, Stephen; Shafto, Mike

2006-01-01

Navigation-knowing where one is and finding a safe route-is a fundamental aspect of all exploration. In unfamiliar terrain, one may use maps and instruments such as a compass or binoculars to assist, and people often collaborate in finding their way. This paper analyzes a group of people driving a humvee from a base camp to the north coast of Devon Island in the High Canadian Arctic. A complete audio recording and video during most stops allows a quantitative and semantic analysis of the conversations when the team stopped to take bearings and replan a route. Over a period of 2 hours, the humvee stopped 20 times, with an average duration of 3.15 min/pause and 3.85 min moving forward. The team failed to reach its goal due to difficult terrain causing mechanical problems. The analysis attempts to explain these facts by considering a variety of complicating factors, especially the navigation problem of relating maps and the world to locate the humvee and to plan a route. The analysis reveals patterns in topic structure and turn-taking, supporting the view that the collaboration was efficient, but the tools and information were inadequate for the task. This work is relevant for planning and training for planetary surface missions, as well as developing computer systems that could aid navigation.

History-based route selection for reactive ad hoc routing protocols

NASA Astrophysics Data System (ADS)

Medidi, Sirisha; Cappetto, Peter

2007-04-01

Ad hoc networks rely on cooperation in order to operate, but in a resource constrained environment not all nodes behave altruistically. Selfish nodes preserve their own resources and do not forward packets not in their own self interest. These nodes degrade the performance of the network, but judicious route selection can help maintain performance despite this behavior. Many route selection algorithms place importance on shortness of the route rather than its reliability. We introduce a light-weight route selection algorithm that uses past behavior to judge the quality of a route rather than solely on the length of the route. It draws information from the underlying routing layer at no extra cost and selects routes with a simple algorithm. This technique maintains this data in a small table, which does not place a high cost on memory. History-based route selection's minimalism suits the needs the portable wireless devices and is easy to implement. We implemented our algorithm and tested it in the ns2 environment. Our simulation results show that history-based route selection achieves higher packet delivery and improved stability than its length-based counterpart.

Strategic planning for disaster recovery with stochastic last mile distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Russell Whitford; Van Hentenryck, Pascal; Coffrin, Carleton

2010-01-01

This paper considers the single commodity allocation problem (SCAP) for disaster recovery, a fundamental problem faced by all populated areas. SCAPs are complex stochastic optimization problems that combine resource allocation, warehouse routing, and parallel fleet routing. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This paper formalizes the specification of SCAPs and introduces a novel multi-stage hybrid-optimization algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. The algorithm was validated on hurricane disaster scenarios generated by Los Alamos National Laboratory using state-of-the-art disaster simulation toolsmore » and is deployed to aid federal organizations in the US.« less

Optimal Integration of Departure and Arrivals in Terminal Airspace

NASA Technical Reports Server (NTRS)

Xue, Min; Zelinski, Shannon Jean

2012-01-01

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

Reconfigurable routing protocol for free space optical sensor networks.

PubMed

Xie, Rong; Yang, Won-Hyuk; Kim, Young-Chon

2012-01-01

Recently, free space optical sensor networks (FSOSNs), which are based on free space optics (FSO) instead of radio frequency (RF), have gained increasing visibility over traditional wireless sensor networks (WSNs) due to their advantages such as larger capacity, higher security, and lower cost. However, the performance of FSOSNs is restricted to the requirement of a direct line-of-sight (LOS) path between a sender and a receiver pair. Once a node dies of energy depletion, the network would probably suffer from a dramatic decrease of connectivity, resulting in a huge loss of data packets. Thus, this paper proposes a reconfigurable routing protocol (RRP) to overcome this problem by dynamically reconfiguring the network virtual topology. The RRP works in three phases: (1) virtual topology construction, (2) routing establishment, and (3) reconfigurable routing. When data transmission begins, the data packets are first routed through the shortest hop paths. Then a reconfiguration is initiated by the node whose residual energy falls below a threshold. Nodes affected by this dying node are classified into two types, namely maintenance nodes and adjustment nodes, and they are reconfigured according to the types. An energy model is designed to evaluate the performance of RRP through OPNET simulation. Our simulation results indicate that the RRP achieves better performance compared with the simple-link protocol and a direct reconfiguration scheme in terms of connectivity, network lifetime, packet delivery ratio and the number of living nodes.

Unified heuristics to solve routing problem of reverse logistics in sustainable supply chain

NASA Astrophysics Data System (ADS)

Anbuudayasankar, S. P.; Ganesh, K.; Lenny Koh, S. C.; Mohandas, K.

2010-03-01

A reverse logistics problem, motivated by many real-life applications, is examined where bottles/cans in which products are delivered from a processing depot to customers in one period are available for return to the depot in the following period. The picked-up bottles/cans need to be adjusted in the place of delivery load. This problem is termed as simultaneous delivery and pick-up problem with constrained capacity (SDPC). We develop three unified heuristics based on extended branch and bound heuristic, genetic algorithm and simulated annealing to solve SDPC. These heuristics are also designed to solve standard travelling salesman problem (TSP) and TSP with simultaneous delivery and pick-up (TSDP). We tested the heuristics on standard, derived and randomly generated datasets of TSP, TSDP and SDPC and obtained satisfying results with high convergence in reasonable time.

A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs

PubMed Central

Liu, Wan-Yu; Chou, Chun-Hung

2014-01-01

This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems. PMID:24982990

Busing and Redistricting in the 'Down-Up' Era.

ERIC Educational Resources Information Center

Freeman, David N.

1987-01-01

Besides redistricting problems engendered by higher elementary school enrollments (and decreasing secondary enrollments), school administrators face student transport challenges. Acquiring new routes and larger buses could be costly. This article advances computerized systems as the most cost-effective way to optimize routes and manage…

Vehicle-Routing Optimization for Municipal Solid Waste Collection Using Genetic Algorithm: The Case of Southern Nablus City

NASA Astrophysics Data System (ADS)

Assaf, Ramiz; Saleh, Yahya

2017-09-01

Municipalities are responsible for solid waste collectiont for environmental, social and economic purposes. Practices of municipalities should be effective and efficient, with the objectives of reducing the total incurred costs in the solid waste collection network concurrently achieving the highest service level. This study aims at finding the best routes of solid waste collection network in Nablus city-Palestine. More specifically, the study seeks the optimal route that minimizes the total travelled distance by the trucks and hence the resulted costs. The current situation is evaluated and the problem is modelled as a Vehicle Routing Problem (VRP). The VRP is then optimized via a genetic algorithm. Specifically, compared to the current situation, the trucks total travelled distance was reduced by 66%, whereas the collection time was reduced from 7 hours per truck-trip to 2.3 hours. The findings of this study is useful for all municipality policy makers that are responsible for solid waste collection.

Some factors affecting performance of rats in the traveling salesman problem.

PubMed

Bellizzi, C; Goldsteinholm, K; Blaser, R E

2015-11-01

The traveling salesman problem (TSP) is used to measure the efficiency of spatial route selection. Among researchers in cognitive psychology and neuroscience, it has been utilized to examine the mechanisms of decision making, planning, and spatial navigation. While both human and non-human animals produce good solutions to the TSP, the solution strategies engaged by non-human species are not well understood. We conducted two experiments on the TSP using Long-Evans laboratory rats as subjects. The first experiment examined the role of arena walls in route selection. Rats tend to display thigmotaxis in testing conditions comparable to the TSP, which could produce results similar to a convex hull type strategy suggested for humans. The second experiment examined the role of turn angle between targets along the optimal route, to determine whether rats exhibit a preferential turning bias. Our results indicated that both thigmotaxis and preferential turn angles do affect performance in the TSP, but neither is sufficient as a predictor of route choice in this task.

Short paths in expander graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleinberg, J.; Rubinfeld, R.

Graph expansion has proved to be a powerful general tool for analyzing the behavior of routing algorithms and the interconnection networks on which they run. We develop new routing algorithms and structural results for bounded-degree expander graphs. Our results are unified by the fact that they are all based upon, and extend, a body of work asserting that expanders are rich in short, disjoint paths. In particular, our work has consequences for the disjoint paths problem, multicommodify flow, and graph minor containment. We show: (i) A greedy algorithm for approximating the maximum disjoint paths problem achieves a polylogarithmic approximation ratiomore » in bounded-degree expanders. Although our algorithm is both deterministic and on-line, its performance guarantee is an improvement over previous bounds in expanders. (ii) For a multicommodily flow problem with arbitrary demands on a bounded-degree expander, there is a (1 + {epsilon})-optimal solution using only flow paths of polylogarithmic length. It follows that the multicommodity flow algorithm of Awerbuch and Leighton runs in nearly linear time per commodity in expanders. Our analysis is based on establishing the following: given edge weights on an expander G, one can increase some of the weights very slightly so the resulting shortest-path metric is smooth - the min-weight path between any pair of nodes uses a polylogarithmic number of edges. (iii) Every bounded-degree expander on n nodes contains every graph with O(n/log{sup O(1)} n) nodes and edges as a minor.« less

Efficient Secure and Privacy-Preserving Route Reporting Scheme for VANETs

NASA Astrophysics Data System (ADS)

Zhang, Yuanfei; Pei, Qianwen; Dai, Feifei; Zhang, Lei

2017-10-01

Vehicular ad-hoc network (VANET) is a core component of intelligent traffic management system which could provide various of applications such as accident prediction, route reporting, etc. Due to the problems caused by traffic congestion, route reporting becomes a prospective application which can help a driver to get optimal route to save her travel time. Before enjoying the convenience of route reporting, security and privacy-preserving issues need to be concerned. In this paper, we propose a new secure and privacy-preserving route reporting scheme for VANETs. In our scheme, only an authenticated vehicle can use the route reporting service provided by the traffic management center. Further, a vehicle may receive the response from the traffic management center with low latency and without violating the privacy of the vehicle. Experiment results show that our scheme is much more efficiency than the existing one.

Key management schemes using routing information frames in secure wireless sensor networks

NASA Astrophysics Data System (ADS)

Kamaev, V. A.; Finogeev, A. G.; Finogeev, A. A.; Parygin, D. S.

2017-01-01

The article considers the problems and objectives of key management for data encryption in wireless sensor networks (WSN) of SCADA systems. The structure of the key information in the ZigBee network and methods of keys obtaining are discussed. The use of a hybrid key management schemes is most suitable for WSN. The session symmetric key is used to encrypt the sensor data, asymmetric keys are used to encrypt the session key transmitted from the routing information. Three algorithms of hybrid key management using routing information frames determined by routing methods and the WSN topology are presented.

Developing Gis-Based Demand-Responsive Transit System in Tehran City

NASA Astrophysics Data System (ADS)

Faroqi, H.; Sadeghi-Niaraki, A.

2015-12-01

Create, maintain and development of public transport network in metropolitan are important problems in the field of urban transport management. In public transport, maximize the efficient use of public fleet capacity has been considered. Concepts and technologies of GIS have provided suitable way for management and optimization of the public transports systems. In demand-responsive public transportation system, firstly fellow traveller groups have been established for applicants based on spatial concepts and tools of GIS, second for each group according to its' members and their paths, a public vehicle has been allocated to them then based on dynamic routing, the fellow passenger group has been gathered from their origins and has been moved to their destinations through optimal route. The suggested system has been implemented based on network data and commuting trips statistics of 1 to 6 districts in Tehran city. Evaluation performed on the results show the 34% increase using of Taxi capacity, 13% increase using of Van capacity and 10% increase using of Bus capacity in comparison between current public transport system and suggested public transportation system has been improved.

Geospatial Modelling Approach for Interlinking of Rivers: A Case Study of Vamsadhara and Nagavali River Systems in Srikakulam, Andhra Pradesh

NASA Astrophysics Data System (ADS)

Swathi Lakshmi, A.; Saran, S.; Srivastav, S. K.; Krishna Murthy, Y. V. N.

2014-11-01

India is prone to several natural disasters such as floods, droughts, cyclones, landslides and earthquakes on account of its geoclimatic conditions. But the most frequent and prominent disasters are floods and droughts. So to reduce the impact of floods and droughts in India, interlinking of rivers is one of the best solutions to transfer the surplus flood waters to deficit/drought prone areas. Geospatial modelling provides a holistic approach to generate probable interlinking routes of rivers based on existing geoinformatics tools and technologies. In the present study, SRTM DEM and AWiFS datasets coupled with land-use/land -cover, geomorphology, soil and interpolated rainfall surface maps have been used to identify the potential routes in geospatial domain for interlinking of Vamsadhara and Nagavali River Systems in Srikakulam district, Andhra Pradesh. The first order derivatives are derived from DEM and road, railway and drainage networks have been delineated using the satellite data. The inundation map has been prepared using AWiFS derived Normalized Difference Water Index (NDWI). The Drought prone areas were delineated on the satellite image as per the records declared by Revenue Department, Srikakulam. Majority Rule Based (MRB) aggregation technique is performed to optimize the resolution of obtained data in order to retain the spatial variability of the classes. Analytical Hierarchy Process (AHP) based Multi-Criteria Decision Making (MCDM) is implemented to obtain the prioritization of parameters like geomorphology, soil, DEM, slope, and land use/land-cover. A likelihood grid has been generated and all the thematic layers are overlaid to identify the potential grids for routing optimization. To give a better routing map, impedance map has been generated and several other constraints are considered. The implementation of canal construction needs extra cost in some areas. The developed routing map is published into OGC WMS services using open source GeoServer and proposed routing service can be visualized over Bhuvan portal (http://www.bhuvan.nrsc.gov.in/).Thus the obtained routing map of proposed canals focuses on transferring the surplus waters to drought prone areas to solve the problem of water scarcity, to properly utilize the flood waters for irrigational purposes and also help in recharging of groundwater. Similar methodology can be adopted in other interlinking of river systems.

Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Forouzanfar, Fateme; Ebrahimnejad, Sadoullah

2013-07-01

This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to customer in a stochastic supply chain system, simultaneously. This problem is formulated as a bi-objective stochastic mixed-integer nonlinear programming model. The aim of this model is to determine the number of located distribution centers, their locations, and capacity levels, and allocating customers to distribution centers and distribution centers to suppliers. It also determines the inventory control decisions on the amount of ordered products and the amount of safety stocks at each opened DC, selecting a type of vehicle for transportation. Moreover, it determines routing decisions, such as determination of vehicles' routes starting from an opened distribution center to serve its allocated customers and returning to that distribution center. All are done in a way that the total system cost and the total transportation time are minimized. The Lingo software is used to solve the presented model. The computational results are illustrated in this paper.

Route selection by rats and humans in a navigational traveling salesman problem.

PubMed

Blaser, Rachel E; Ginchansky, Rachel R

2012-03-01

Spatial cognition is typically examined in non-human animals from the perspective of learning and memory. For this reason, spatial tasks are often constrained by the time necessary for training or the capacity of the animal's short-term memory. A spatial task with limited learning and memory demands could allow for more efficient study of some aspects of spatial cognition. The traveling salesman problem (TSP), used to study human visuospatial problem solving, is a simple task with modifiable learning and memory requirements. In the current study, humans and rats were characterized in a navigational version of the TSP. Subjects visited each of 10 baited targets in any sequence from a set starting location. Unlike similar experiments, the roles of learning and memory were purposely minimized; all targets were perceptually available, no distracters were used, and each configuration was tested only once. The task yielded a variety of behavioral measures, including target revisits and omissions, route length, and frequency of transitions between each pair of targets. Both humans and rats consistently chose routes that were more efficient than chance, but less efficient than optimal, and generally less efficient than routes produced by the nearest-neighbor strategy. We conclude that the TSP is a useful and flexible task for the study of spatial cognition in human and non-human animals.

Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

PubMed Central

Leong, Kah Huo; Abdul-Rahman, Hamzah; Wang, Chen; Onn, Chiu Chuen

2016-01-01

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning. PMID:27930659

Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System.

PubMed

Leong, Kah Huo; Abdul-Rahman, Hamzah; Wang, Chen; Onn, Chiu Chuen; Loo, Siaw-Chuing

2016-01-01

Railway and metro transport systems (RS) are becoming one of the popular choices of transportation among people, especially those who live in urban cities. Urbanization and increasing population due to rapid development of economy in many cities are leading to a bigger demand for urban rail transit. Despite being a popular variant of Traveling Salesman Problem (TSP), it appears that the universal formula or techniques to solve the problem are yet to be found. This paper aims to develop an optimization algorithm for optimum route selection to multiple destinations in RS before returning to the starting point. Bee foraging behaviour is examined to generate a reliable algorithm in railway TSP. The algorithm is then verified by comparing the results with the exact solutions in 10 test cases, and a numerical case study is designed to demonstrate the application with large size sample. It is tested to be efficient and effective in railway route planning as the tour can be completed within a certain period of time by using minimal resources. The findings further support the reliability of the algorithm and capability to solve the problems with different complexity. This algorithm can be used as a method to assist business practitioners making better decision in route planning.

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

PubMed

Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

NASA Astrophysics Data System (ADS)

Ramadhani, T.; Hertono, G. F.; Handari, B. D.

2017-07-01

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

Speedy routing recovery protocol for large failure tolerance in wireless sensor networks.

PubMed

Lee, Joa-Hyoung; Jung, In-Bum

2010-01-01

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols.

Routing channels in VLSI layout

NASA Astrophysics Data System (ADS)

Cai, Hong

A number of algorithms for the automatic routing of interconnections in Very Large Scale Integration (VLSI) building-block layouts are presented. Algorithms for the topological definition of channels, the global routing and the geometrical definition of channels are presented. In contrast to traditional approaches the definition and ordering of the channels is done after the global routing. This approach has the advantage that global routing information can be taken into account to select the optimal channel structure. A polynomial algorithm for the channel definition and ordering problem is presented. The existence of a conflict-free channel structure is guaranteed by enforcing a sliceable placement. Algorithms for finding the shortest connection path are described. A separate algorithm is developed for the power net routing, because the two power nets must be planarly routed with variable wire width. An integrated placement and routing system for generating building-block layout is briefly described. Some experimental results and design experiences in using the system are also presented. Very good results are obtained.

The Potential for Additional Channel Airlift in a Low Cargo Demand Theater

DTIC Science & Technology

2014-06-13

benefit of providing additional channel airlift in the AFRICOM Theater. Assumptions/Limitations The research problem has many variables, so the... salesman USTRANSCOM via AMC has a variety of airlift services it can offer its customers. Annex 3-17 Air Mobility Operations defines airlift as...International, 2008) Given the trouble land based travel offers the alternative for military operations is to route cargo and personnel by air. Air

A Routing Protocol for Multisink Wireless Sensor Networks in Underground Coalmine Tunnels

PubMed Central

Xia, Xu; Chen, Zhigang; Liu, Hui; Wang, Huihui; Zeng, Feng

2016-01-01

Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks. PMID:27916917

A Routing Protocol for Multisink Wireless Sensor Networks in Underground Coalmine Tunnels.

PubMed

Xia, Xu; Chen, Zhigang; Liu, Hui; Wang, Huihui; Zeng, Feng

2016-11-30

Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks.

Cognitive process modelling of controllers in en route air traffic control.

PubMed

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

Automated Conflict Resolution, Arrival Management and Weather Avoidance for ATM

NASA Technical Reports Server (NTRS)

Erzberger, H.; Lauderdale, Todd A.; Chu, Yung-Cheng

2010-01-01

The paper describes a unified solution to three types of separation assurance problems that occur in en-route airspace: separation conflicts, arrival sequencing, and weather-cell avoidance. Algorithms for solving these problems play a key role in the design of future air traffic management systems such as NextGen. Because these problems can arise simultaneously in any combination, it is necessary to develop integrated algorithms for solving them. A unified and comprehensive solution to these problems provides the foundation for a future air traffic management system that requires a high level of automation in separation assurance. The paper describes the three algorithms developed for solving each problem and then shows how they are used sequentially to solve any combination of these problems. The first algorithm resolves loss-of-separation conflicts and is an evolution of an algorithm described in an earlier paper. The new version generates multiple resolutions for each conflict and then selects the one giving the least delay. Two new algorithms, one for sequencing and merging of arrival traffic, referred to as the Arrival Manager, and the other for weather-cell avoidance are the major focus of the paper. Because these three problems constitute a substantial fraction of the workload of en-route controllers, integrated algorithms to solve them is a basic requirement for automated separation assurance. The paper also reviews the Advanced Airspace Concept, a proposed design for a ground-based system that postulates redundant systems for separation assurance in order to achieve both high levels of safety and airspace capacity. It is proposed that automated separation assurance be introduced operationally in several steps, each step reducing controller workload further while increasing airspace capacity. A fast time simulation was used to determine performance statistics of the algorithm at up to 3 times current traffic levels.

Logistical management and private sector involvement in reducing the cost of municipal solid waste collection service in the Tubas area of the West Bank.

PubMed

El-Hamouz, Amer M

2008-01-01

This paper addresses the problems of the municipal solid waste (MSW) collection system in the Tubas district of Palestine. More specifically, it addresses the often-voiced concerns pertaining to low efficiency as well as environmental problems. This was carried out through a systematic methodological approach. The paper illustrates how a private company applied a logistical management strategy, by rescheduling the MSW collection system, reallocating street solid waste containers and minimizing vehicle routing. The way in which the MSW collection timetable was rescheduled decreased the operating expenses and thus reduced MSW collection costs. All data needed to reschedule the collection timetable and optimize vehicle routing were based on actual field measurements. The new MSW collection timetable introduced by a private company was monitored for a period of a month. The new system resulted in an improvement in the MSW collection system by reducing the collection cost to a level that is socially acceptable (US dollars 3.75/family/month), as well as economically and environmentally sound.

Field studies on pesticides and birds: Unexpected and unique relations

USGS Publications Warehouse

Blus, L.J.; Henny, Charles J.

1997-01-01

We review the advantages and disadvantages of experimental and field studies for determining effects of pesticides on birds. Important problems or principles initially discovered in the field include effects of DDT (through its metabolite DDE) on eggshell thickness, reproductive success, and population stability; trophic-level bioaccumulation of the lipid-soluble organochlorine pesticides; indirect effects on productivity and survival through reductions in the food supply and cover by herbicides and insecticides; unexpected toxic effects and routes of exposure of organophosphorus compounds such as famphur and dimethoate; effects related to simultaneous application at full strength of several pesticides of different classes; and others. Also, potentially serious bird problems with dicofol, based on laboratory studies, later proved negligible in the field. In refining field tests of pesticides, the selection of a species or group of species to study is important, because exposure routes may vary greatly, and 10-fold interspecific differences in sensitivity to pesticides are relatively common. Although there are limitations with field investigations, particularly uncontrollable variables that must be addressed, the value of a well-designed field study far outweighs its shortcomings.

Field studies on pesticides and birds: unexpected and unique relations

USGS Publications Warehouse

Blus, L.J.; Henny, C.J.

1997-01-01

We review the advantages and disadvantages of experimental and field studies for determining effects of pesticides on birds. Important problems or principles initially discovered in the field include effects of DDT (through its metabolite DDE) on eggshell thickness, reproductive success, and population stability; trophic-level bioaccumulation of the lipid-soluble organochlorine pesticides; indirect effects on productivity and survival through reductions in the food supply and cover by herbicides and insecticides; unexpected toxic effects and routes of exposure of organophosphorus compounds such as famphur and dimethoate; effects related to simultaneous application at full strength of several pesticides of different classes; and others. Also, potentially serious bird problems with dicofol, based on laboratory studies, later proved negligible in the field. In refining field tests of pesticides, the selection of a species or group of species to study is important, because exposure routes may vary greatly, and 10-fold interspecific differences in sensitivity to pesticides are relatively common. Although there are limitations with field investigations, particularly uncontrollable variables that must be addressed, the value of a well-designed field study far outweighs its shortcomings

Radar Tracking and Motion-Sensitive Cameras on Flowers Reveal the Development of Pollinator Multi-Destination Routes over Large Spatial Scales

PubMed Central

Reynolds, Andrew M.; Stelzer, Ralph J.; Lim, Ka S.; Smith, Alan D.; Osborne, Juliet L.; Chittka, Lars

2012-01-01

Central place foragers, such as pollinating bees, typically develop circuits (traplines) to visit multiple foraging sites in a manner that minimizes overall travel distance. Despite being taxonomically widespread, these routing behaviours remain poorly understood due to the difficulty of tracking the foraging history of animals in the wild. Here we examine how bumblebees (Bombus terrestris) develop and optimise traplines over large spatial scales by setting up an array of five artificial flowers arranged in a regular pentagon (50 m side length) and fitted with motion-sensitive video cameras to determine the sequence of visitation. Stable traplines that linked together all the flowers in an optimal sequence were typically established after a bee made 26 foraging bouts, during which time only about 20 of the 120 possible routes were tried. Radar tracking of selected flights revealed a dramatic decrease by 80% (ca. 1500 m) of the total travel distance between the first and the last foraging bout. When a flower was removed and replaced by a more distant one, bees engaged in localised search flights, a strategy that can facilitate the discovery of a new flower and its integration into a novel optimal trapline. Based on these observations, we developed and tested an iterative improvement heuristic to capture how bees could learn and refine their routes each time a shorter route is found. Our findings suggest that complex dynamic routing problems can be solved by small-brained animals using simple learning heuristics, without the need for a cognitive map. PMID:23049479

Optimal routing of hazardous substances in time-varying, stochastic transportation networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.

This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Severalmore » specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions.« less

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon C.; Zhu, Zhifan; Jeong, Myeongsook; Kim, Hyounkong; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon Chul; Zhu, Zhifan; Jeong, Myeong-Sook; Kim, Hyoun Kyoung; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks.

PubMed

Raza, Waseem; Arshad, Farzana; Ahmed, Imran; Abdul, Wadood; Ghouzali, Sanaa; Niaz, Iftikhar Azim; Javaid, Nadeem

2016-11-04

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.

A patient with aphasia using the nonsemantic lexical route for Kanji reading.

PubMed

Hashimoto, Kosei; Uno, Akira; Sambai, Ami; Mizumoto, Go

We report a patient with aphasia, caused by cerebral hemorrhage, who probably used the nonsemantic lexical route when reading words aloud. To investigate the mechanisms underlying her reading dysfunction, we analyzed her reading abilities using the Dual-Route Cascaded Model. Language tests resulted in low correct percentages for both reading comprehension and reading nonwords aloud, suggesting problems in the semantic system and the nonlexical route. Conversely, the patient showed high scores on the reading words aloud task. Although she failed to understand many inconsistent-atypical words in the reading comprehension test, she correctly read most words aloud, suggesting that she used the nonsemantic lexical route. In addition, the lexical reading route was analyzed in detail by using inconsistent-atypical Kanji words as stimuli. Finally, we analyzed her reading dysfunction compared with previous cases.

Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence

NASA Astrophysics Data System (ADS)

Muraleedharan, Rajani; Ye, Xiang; Osadciw, Lisa Ann

2008-04-01

Security in wireless sensor networks is typically sacrificed or kept minimal due to limited resources such as memory and battery power. Hence, the sensor nodes are prone to Denial-of-service attacks and detecting the threats is crucial in any application. In this paper, the Sybil attack is analyzed and a novel prediction method, combining Bayesian algorithm and Swarm Intelligence (SI) is proposed. Bayesian Networks (BN) is used in representing and reasoning problems, by modeling the elements of uncertainty. The decision from the BN is applied to SI forming an Hybrid Intelligence Scheme (HIS) to re-route the information and disconnecting the malicious nodes in future routes. A performance comparison based on the prediction using HIS vs. Ant System (AS) helps in prioritizing applications where decisions are time-critical.

Domestic Disasters and Geospatial Technology for the Defense Logistics Agency

DTIC Science & Technology

2014-12-01

total distance traveled and satisfy all fuel demands. This report used the Vehicle Routing Problem (VRP) Spreadsheet Solver, developed by Erdogan ...Security Affairs, 2(2), 5–10. Erdogan , G. (2013). VRP spreadsheet solver. Retrieved from VeRoLog: EURO Working Group on Vehicle Routing and Logistics

Routing in Networks with Random Topologies

NASA Technical Reports Server (NTRS)

Bambos, Nicholas

1997-01-01

We examine the problems of routing and server assignment in networks with random connectivities. In such a network the basic topology is fixed, but during each time slot and for each of tis input queues, each server (node) is either connected to or disconnected from each of its queues with some probability.

A chance-constrained stochastic approach to intermodal container routing problems.

PubMed

Zhao, Yi; Liu, Ronghui; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost.

A chance-constrained stochastic approach to intermodal container routing problems

PubMed Central

Zhao, Yi; Zhang, Xi; Whiteing, Anthony

2018-01-01

We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic transfer time, with the objective of minimising the expected total cost. Two chance constraints are proposed to ensure that the container service satisfies ship fulfilment and cargo on-time delivery with pre-specified probabilities. A hybrid heuristic algorithm is employed to solve the binary integer chance-constrained programming model. Two case studies are conducted to demonstrate the feasibility of the proposed model and to analyse the impact of stochastic variables and chance-constraints on the optimal solution and total cost. PMID:29438389

Enhancement of Beaconless Location-Based Routing with Signal Strength Assistance for Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Chen, Guowei; Itoh, Kenichi; Sato, Takuro

Routing in Ad-hoc networks is unreliable due to the mobility of the nodes. Location-based routing protocols, unlike other protocols which rely on flooding, excel in network scalability. Furthermore, new location-based routing protocols, like, e. g. BLR [1], IGF [2], & CBF [3] have been proposed, with the feature of not requiring beacons in MAC-layer, which improve more in terms of scalability. Such beaconless routing protocols can work efficiently in dense network areas. However, these protocols' algorithms have no ability to avoid from routing into sparse areas. In this article, historical signal strength has been added as a factor into the BLR algorithm, which avoids routing into sparse area, and consequently improves the global routing efficiency.

Bellman Ford algorithm - in Routing Information Protocol (RIP)

NASA Astrophysics Data System (ADS)

Krianto Sulaiman, Oris; Mahmud Siregar, Amir; Nasution, Khairuddin; Haramaini, Tasliyah

2018-04-01

In a large scale network need a routing that can handle a lot number of users, one of the solutions to cope with large scale network is by using a routing protocol, There are 2 types of routing protocol that is static and dynamic, Static routing is manually route input based on network admin, while dynamic routing is automatically route input formed based on existing network. Dynamic routing is efficient used to network extensively because of the input of route automatic formed, Routing Information Protocol (RIP) is one of dynamic routing that uses the bellman-ford algorithm where this algorithm will search for the best path that traversed the network by leveraging the value of each link, so with the bellman-ford algorithm owned by RIP can optimize existing networks.

Exploring Maps with Greedy Navigators

NASA Astrophysics Data System (ADS)

Lee, Sang Hoon; Holme, Petter

2012-03-01

During the last decade of network research focusing on structural and dynamical properties of networks, the role of network users has been more or less underestimated from the bird’s-eye view of global perspective. In this era of global positioning system equipped smartphones, however, a user’s ability to access local geometric information and find efficient pathways on networks plays a crucial role, rather than the globally optimal pathways. We present a simple greedy spatial navigation strategy as a probe to explore spatial networks. These greedy navigators use directional information in every move they take, without being trapped in a dead end based on their memory about previous routes. We suggest that the centralities measures have to be modified to incorporate the navigators’ behavior, and present the intriguing effect of navigators’ greediness where removing some edges may actually enhance the routing efficiency, which is reminiscent of Braess’s paradox. In addition, using samples of road structures in large cities around the world, it is shown that the navigability measure we define reflects unique structural properties, which are not easy to predict from other topological characteristics. In this respect, we believe that our routing scheme significantly moves the routing problem on networks one step closer to reality, incorporating the inevitable incompleteness of navigators’ information.

Understanding Route Aggregation

DTIC Science & Technology

2010-03-09

routing anomalies, and is fingered to be the cause of many reported loops and blackholes . In this paper, we posit that the problem arises from a lack of...Route aggre- gation can also result in blackholes [18], which are surprisingly prevalent in the Internet [11]. We illustrate these known anomalies with...advertisement Forwarding paths A B C 10.1.30.0/24 10.1.16.0/22 10.1.16.0/2010.1.16.0/20 Figure 4: Illustration of a blackhole . forwards the packet to Y

More arrows in the quiver: new pathways and old problems with heavy alkaline earth metal diphenylmethanides.

PubMed

Alexander, Jacob S; Ruhlandt-Senge, Karin

2004-03-05

Progress in the field of sigma-bonded alkaline earth organometallics has been handicapped by numerous complications, such as high reactivity, low solubility, and the limited availability of suitable starting materials. Here we present two synthetic methods, hydrocarbon elimination and desilylation, as alternative routes into this chemistry. A novel barium diphenylmethanide was prepared using these routes delineating that both methods provide a powerful, versatile synthetic access route to an extended library of organometallic alkaline earth derivatives.

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

A Systems Approach to the Aeromedical Aircraft Routing Problem Using a Computer-Based Model.

DTIC Science & Technology

1988-01-01

subscriber) and immediate (dynamic) service requests are generated . The DOD system is similar in many respects to urban paratransit systems for the...desired destination. This required us to develop effective service criteria,2 rules for ’storino’ patients overnight at enroute locations, and schemes ...a planning subsystem has to deal with the generation of plans for the system. ... The management sets the component goals, allocates the resources,and

Energy Remote Sensing Applications Projects at the NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Norman, S. D.; Likens, W. C.; Mouat, D. A.

1982-01-01

The NASA Ames Research Center is active in energy projects primarily in the role of providing assistance to users in the solution of a number of problems related to energy. Data bases were produced which can be used, in combination with other sources of information, to solve spatially related energy problems. Six project activities at Ames are described which relate to energy and remote sensing. Two projects involve power demand forecasting and estimations using remote sensing and geographic information systems; two others involve transmission line routing and corridor analysis; one involves a synfuel user needs assessment through remote sensing; and the sixth involves the siting of energy facilities.

Fleet Assignment Using Collective Intelligence

NASA Technical Reports Server (NTRS)

Antoine, Nicolas E.; Bieniawski, Stefan R.; Kroo, Ilan M.; Wolpert, David H.

2004-01-01

Airline fleet assignment involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of an agent-based integer optimization algorithm to a "cold start" fleet assignment problem. Results show that the optimizer can successfully solve such highly- constrained problems (129 variables, 184 constraints).

Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited

NASA Astrophysics Data System (ADS)

Lee, Youngseok; Mukherjee, Biswanath

2004-03-01

Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.

An emergency-adaptive routing scheme for wireless sensor networks for building fire hazard monitoring.

PubMed

Zeng, Yuanyuan; Sreenan, Cormac J; Sitanayah, Lanny; Xiong, Naixue; Park, Jong Hyuk; Zheng, Guilin

2011-01-01

Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work.

An Emergency-Adaptive Routing Scheme for Wireless Sensor Networks for Building Fire Hazard Monitoring

PubMed Central

Zeng, Yuanyuan; Sreenan, Cormac J.; Sitanayah, Lanny; Xiong, Naixue; Park, Jong Hyuk; Zheng, Guilin

2011-01-01

Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work. PMID:22163774

Relationship among Environmental Pointing Accuracy, Mental Rotation, Sex, and Hormones

ERIC Educational Resources Information Center

Bell, Scott; Saucier, Deborah

2004-01-01

Humans rely on internal representations to solve a variety of spatial problems including navigation. Navigation employs specific information to compose a representation of space that is distinct from that obtained through static bird's-eye or horizontal perspectives. The ability to point to on-route locations, off-route locations, and the route…

Some principles governing the establishment of meteorological stations along air routes

NASA Technical Reports Server (NTRS)

Aujames, P

1922-01-01

The organization of a meteorological service for an air route involves the solution of two distinct problems: distribution and grouping of meteorological stations and communications. Experience gained in the establishment of two lines, Paris-Warsaw and Constantinople-Bucharest enables us to establish certain principles, which may be of interest to note here.

Location and Routing of the Defense Courier Service Aerial Network

DTIC Science & Technology

1991-03-01

12 Coefficient Determinatior .................... . .15 Heuristic Solution Techniques ................... 16 Space Filling Curves ...178 V List of Figures Figure Page I. Space Filling Curves ............................. 2. The Sweep Heuristic...frequency associated with the most served site within a given depot’s route system (18). Approach to the Problem The research involves several phases . In

Municipal solid waste transportation optimisation with vehicle routing approach: case study of Pontianak City, West Kalimantan

NASA Astrophysics Data System (ADS)

Kamal, M. A.; Youlla, D.

2018-03-01

Municipal solid waste (MSW) transportation in Pontianak City becomes an issue that need to be tackled by the relevant agencies. The MSW transportation service in Pontianak City currently requires very high resources especially in vehicle usage. Increasing the number of fleets has not been able to increase service levels while garbage volume is growing every year along with population growth. In this research, vehicle routing optimization approach was used to find optimal and efficient routes of vehicle cost in transporting garbage from several Temporary Garbage Dump (TGD) to Final Garbage Dump (FGD). One of the problems of MSW transportation is that there is a TGD which exceed the the vehicle capacity and must be visited more than once. The optimal computation results suggest that the municipal authorities only use 3 vehicles from 5 vehicles provided with the total minimum cost of IDR. 778,870. The computation time to search optimal route and minimal cost is very time consuming. This problem is influenced by the number of constraints and decision variables that have are integer value.

Dynamic multicast routing scheme in WDM optical network

NASA Astrophysics Data System (ADS)

Zhu, Yonghua; Dong, Zhiling; Yao, Hong; Yang, Jianyong; Liu, Yibin

2007-11-01

During the information era, the Internet and the service of World Wide Web develop rapidly. Therefore, the wider and wider bandwidth is required with the lower and lower cost. The demand of operation turns out to be diversified. Data, images, videos and other special transmission demands share the challenge and opportunity with the service providers. Simultaneously, the electrical equipment has approached their limit. So the optical communication based on the wavelength division multiplexing (WDM) and the optical cross-connects (OXCs) shows great potentials and brilliant future to build an optical network based on the unique technical advantage and multi-wavelength characteristic. In this paper, we propose a multi-layered graph model with inter-path between layers to solve the problem of multicast routing wavelength assignment (RWA) contemporarily by employing an efficient graph theoretic formulation. And at the same time, an efficient dynamic multicast algorithm named Distributed Message Copying Multicast (DMCM) mechanism is also proposed. The multicast tree with minimum hops can be constructed dynamically according to this proposed scheme.

Tuple spaces in hardware for accelerated implicit routing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Zachary Kent; Tripp, Justin

2010-12-01

Organizing and optimizing data objects on networks with support for data migration and failing nodes is a complicated problem to handle as systems grow. The goal of this work is to demonstrate that high levels of speedup can be achieved by moving responsibility for finding, fetching, and staging data into an FPGA-based network card. We present a system for implicit routing of data via FPGA-based network cards. In this system, data structures are requested by name, and the network of FPGAs finds the data within the network and relays the structure to the requester. This is acheived through successive examinationmore » of hardware hash tables implemented in the FPGA. By avoiding software stacks between nodes, the data is quickly fetched entirely through FPGA-FPGA interaction. The performance of this system is orders of magnitude faster than software implementations due to the improved speed of the hash tables and lowered latency between the network nodes.« less

Intelligent routing protocol for ad hoc wireless network

NASA Astrophysics Data System (ADS)

Peng, Chaorong; Chen, Chang Wen

2006-05-01

A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage mechanisms, which are used to control active route and reduce the traffic amount in the route discovery procedure. Finial, the numerical experiments are given to show the effectiveness of IRP routing protocol.

Improving Transportation Services for the University of the Thai Chamber of Commerce: A Case Study on Solving the Mixed-Fleet Vehicle Routing Problem with Split Deliveries

NASA Astrophysics Data System (ADS)

Suthikarnnarunai, N.; Olinick, E.

2009-01-01

We present a case study on the application of techniques for solving the Vehicle Routing Problem (VRP) to improve the transportation service provided by the University of The Thai Chamber of Commerce to its staff. The problem is modeled as VRP with time windows, split deliveries, and a mixed fleet. An exact algorithm and a heuristic solution procedure are developed to solve the problem and implemented in the AMPL modeling language and CPLEX Integer Programming solver. Empirical results indicate that the heuristic can find relatively good solutions in a small fraction of the time required by the exact method. We also perform sensitivity analysis and find that a savings in outsourcing cost can be achieved with a small increase in vehicle capacity.

Applying an MVC Framework for The System Development Life Cycle with Waterfall Model Extended

NASA Astrophysics Data System (ADS)

Hardyanto, W.; Purwinarko, A.; Sujito, F.; Masturi; Alighiri, D.

2017-04-01

This paper describes the extension of the waterfall model using MVC architectural pattern for software development. The waterfall model is the based model of the most widely used in software development, yet there are still many problems in it. The general issue usually happens on data changes that cause the delays on the process itself. On the other hand, the security factor on the software as well as one of the major problems. This study uses PHP programming language for implementation. Although this model can be implemented in several programming languages with the same concept. This study is based on MVC architecture so that it can improve the performance of both software development and maintenance, especially concerning security, validation, database access, and routing.

Tour Recommendation Guide- Personalized travel sequence recommendation

NASA Astrophysics Data System (ADS)

Sivakumar, Akshitha; Prabadevi, B.

2017-11-01

Presents a personalized travel sequence for the given area the individual wants to visit. It not only helps to personalize the travel but also recommend a travel sequence based on the area mentioned. Firstly the frequently visited routes are ranked then top ranked routes are chosen based on previous travel records. The data is being collected using data mining and the famous routes are ranked based on user and the route. It helps in bridging the gap between user travel preference and routes.

Biased random key genetic algorithm with insertion and gender selection for capacitated vehicle routing problem with time windows

NASA Astrophysics Data System (ADS)

Rochman, Auliya Noor; Prasetyo, Hari; Nugroho, Munajat Tri

2017-06-01

Vehicle Routing Problem (VRP) often occurs when the manufacturers need to distribute their product to some customers/outlets. The distribution process is typically restricted by the capacity of the vehicle and the working hours at the distributor. This type of VRP is also known as Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A Biased Random Key Genetic Algorithm (BRKGA) was designed and coded in MATLAB to solve the CVRPTW case of soft drink distribution. The standard BRKGA was then modified by applying chromosome insertion into the initial population and defining chromosome gender for parent undergoing crossover operation. The performance of the established algorithms was then compared to a heuristic procedure for solving a soft drink distribution. Some findings are revealed (1) the total distribution cost of BRKGA with insertion (BRKGA-I) results in a cost saving of 39% compared to the total cost of heuristic method, (2) BRKGA with the gender selection (BRKGA-GS) could further improve the performance of the heuristic method. However, the BRKGA-GS tends to yield worse results compared to that obtained from the standard BRKGA.

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks.

PubMed

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-Hoon

2017-05-22

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads.

Multicasting for all-optical multifiber networks

NASA Astrophysics Data System (ADS)

Kã¶Ksal, Fatih; Ersoy, Cem

2007-02-01

All-optical wavelength-routed WDM WANs can support the high bandwidth and the long session duration requirements of the application scenarios such as interactive distance learning or on-line diagnosis of patients simultaneously in different hospitals. However, multifiber and limited sparse light splitting and wavelength conversion capabilities of switches result in a difficult optimization problem. We attack this problem using a layered graph model. The problem is defined as a k-edge-disjoint degree-constrained Steiner tree problem for routing and fiber and wavelength assignment of k multicasts. A mixed integer linear programming formulation for the problem is given, and a solution using CPLEX is provided. However, the complexity of the problem grows quickly with respect to the number of edges in the layered graph, which depends on the number of nodes, fibers, wavelengths, and multicast sessions. Hence, we propose two heuristics layered all-optical multicast algorithm [(LAMA) and conservative fiber and wavelength assignment (C-FWA)] to compare with CPLEX, existing work, and unicasting. Extensive computational experiments show that LAMA's performance is very close to CPLEX, and it is significantly better than existing work and C-FWA for nearly all metrics, since LAMA jointly optimizes routing and fiber-wavelength assignment phases compared with the other candidates, which attack the problem by decomposing two phases. Experiments also show that important metrics (e.g., session and group blocking probability, transmitter wavelength, and fiber conversion resources) are adversely affected by the separation of two phases. Finally, the fiber-wavelength assignment strategy of C-FWA (Ex-Fit) uses wavelength and fiber conversion resources more effectively than the First Fit.

a New Multimodal Multi-Criteria Route Planning Model by Integrating a Fuzzy-Ahp Weighting Method and a Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Ghaderi, F.; Pahlavani, P.

2015-12-01

A multimodal multi-criteria route planning (MMRP) system provides an optimal multimodal route from an origin point to a destination point considering two or more criteria in a way this route can be a combination of public and private transportation modes. In this paper, the simulate annealing (SA) and the fuzzy analytical hierarchy process (fuzzy AHP) were combined in order to find this route. In this regard, firstly, the effective criteria that are significant for users in their trip were determined. Then the weight of each criterion was calculated using the fuzzy AHP weighting method. The most important characteristic of this weighting method is the use of fuzzy numbers that aids the users to consider their uncertainty in pairwise comparison of criteria. After determining the criteria weights, the proposed SA algorithm were used for determining an optimal route from an origin to a destination. One of the most important problems in a meta-heuristic algorithm is trapping in local minima. In this study, five transportation modes, including subway, bus rapid transit (BRT), taxi, walking, and bus were considered for moving between nodes. Also, the fare, the time, the user's bother, and the length of the path were considered as effective criteria for solving the problem. The proposed model was implemented in an area in centre of Tehran in a GUI MATLAB programming language. The results showed a high efficiency and speed of the proposed algorithm that support our analyses.

Does the route of immunoglobin replacement therapy impact quality of life and satisfaction in patients with primary immunodeficiency? Insights from the French cohort "Visages".

PubMed

Bienvenu, B; Cozon, G; Hoarau, C; Pasquet, M; Cherin, P; Clerson, P; Hachulla, E; Crave, J C; Delain, J C; Jaussaud, R

2016-06-22

IgG replacement therapy (IgRT) in primary immunodeficiencies (PID) is a lifelong treatment which may be administered intravenously (IVIg) or subcutaneously (SCIg), at hospital or at home. The objective of the VISAGE study was to investigate if route and/or place for IgRT impact patients' satisfaction regarding IgRT and quality of life (QoL) in real-life conditions. The study enrolled PID patients at least 15 years old receiving IgRT for at least 3 months. Satisfaction and QoL were evaluated at enrollment and over a 12-month follow-up period by Life Quality Index (LQI) which measures 3 dimensions of satisfaction: treatment interference, therapy related problems and therapy settings (factors I, II and III) and SF-36 v2 questionnaire. The study included 116 PID patients (mean age 42 ± 18 years, 44 % males, 58 % with scholar or professional occupation) receiving IgRT for a mean of 8.5 ± 8.4 years. At enrollment they were receiving either home-based SCIg (51 %), hospital-based IVIg (40 %) or home-based IVIg (9 %). Patients exhibited a high degree of satisfaction regarding IgRT whatever the route and place for administration. LQI factor I was higher for home-based SCIg (86 ± 2) than for hospital-based IVIg (81 ± 3) and home-based IVIg (73 ± 5; p = 0.02 versus home-based SCIg); no difference was found for LQI factor II; LQI factor III was higher for home-based SCIg (92 ± 2) than for hospital-based IVIg (87 ± 5) and hospital-based IVIg (82 ± 3; p = 0.005 versus home-based SCIg). By contrast, every dimension of QoL was impaired. Over the follow-up period, 10 patients switched from hospital-based IVIg to home-based SCIg and improved LQI factor I (p = 0.004) and factor III (p = 0.02), while no change was noticed in LQI factors II and QoL. Meanwhile, no change in satisfaction or QoL was found in patients with stable route of IgRT. When asked on their preferred place of treatment all but one patient with home-based treatment would choose to be treated at home and 29 % of patients treated at hospital would prefer home-based IgRT. PID patients expressed a high degree of satisfaction regarding IgRT, contrasting with impaired QoL. In real-life conditions awareness of patient's expectations regarding the route or place of IgRT may be associated with further improvement of satisfaction.

Design of a universal logic block for fault-tolerant realization of any logic operation in trapped-ion quantum circuits

NASA Astrophysics Data System (ADS)

Goudarzi, H.; Dousti, M. J.; Shafaei, A.; Pedram, M.

2014-05-01

This paper presents a physical mapping tool for quantum circuits, which generates the optimal universal logic block (ULB) that can, on average, perform any logical fault-tolerant (FT) quantum operations with the minimum latency. The operation scheduling, placement, and qubit routing problems tackled by the quantum physical mapper are highly dependent on one another. More precisely, the scheduling solution affects the quality of the achievable placement solution due to resource pressures that may be created as a result of operation scheduling, whereas the operation placement and qubit routing solutions influence the scheduling solution due to resulting distances between predecessor and current operations, which in turn determines routing latencies. The proposed flow for the quantum physical mapper captures these dependencies by applying (1) a loose scheduling step, which transforms an initial quantum data flow graph into one that explicitly captures the no-cloning theorem of the quantum computing and then performs instruction scheduling based on a modified force-directed scheduling approach to minimize the resource contention and quantum circuit latency, (2) a placement step, which uses timing-driven instruction placement to minimize the approximate routing latencies while making iterative calls to the aforesaid force-directed scheduler to correct scheduling levels of quantum operations as needed, and (3) a routing step that finds dynamic values of routing latencies for the qubits. In addition to the quantum physical mapper, an approach is presented to determine the single best ULB size for a target quantum circuit by examining the latency of different FT quantum operations mapped onto different ULB sizes and using information about the occurrence frequency of operations on critical paths of the target quantum algorithm to weigh these latencies. Experimental results show an average latency reduction of about 40 % compared to previous work.

The cost of simplifying air travel when modeling disease spread.

PubMed

Lessler, Justin; Kaufman, James H; Ford, Daniel A; Douglas, Judith V

2009-01-01

Air travel plays a key role in the spread of many pathogens. Modeling the long distance spread of infectious disease in these cases requires an air travel model. Highly detailed air transportation models can be over determined and computationally problematic. We compared the predictions of a simplified air transport model with those of a model of all routes and assessed the impact of differences on models of infectious disease. Using U.S. ticket data from 2007, we compared a simplified "pipe" model, in which individuals flow in and out of the air transport system based on the number of arrivals and departures from a given airport, to a fully saturated model where all routes are modeled individually. We also compared the pipe model to a "gravity" model where the probability of travel is scaled by physical distance; the gravity model did not differ significantly from the pipe model. The pipe model roughly approximated actual air travel, but tended to overestimate the number of trips between small airports and underestimate travel between major east and west coast airports. For most routes, the maximum number of false (or missed) introductions of disease is small (<1 per day) but for a few routes this rate is greatly underestimated by the pipe model. If our interest is in large scale regional and national effects of disease, the simplified pipe model may be adequate. If we are interested in specific effects of interventions on particular air routes or the time for the disease to reach a particular location, a more complex point-to-point model will be more accurate. For many problems a hybrid model that independently models some frequently traveled routes may be the best choice. Regardless of the model used, the effect of simplifications and sensitivity to errors in parameter estimation should be analyzed.

Personalized Alert Notifications and Evacuation Routes in Indoor Environments

PubMed Central

Aedo, Ignacio; Yu, Shuxin; Díaz, Paloma; Acuña, Pablo; Onorati, Teresa

2012-01-01

The preparedness phase is crucial in the emergency management process for reaching an adequate level of readiness to react to potential threats and hazards. During this phase, emergency plans are developed to establish, among other procedures, evacuation and emergency escape routes. Information and Communication Technologies (ICT) can support and improve these procedures providing appropriate, updated and accessible information to all people in the affected zone. Current emergency management and evacuation systems do not adapt information to the context and the profile of each person, so messages received in the emergency might be useless. In this paper, we propose a set of criteria that ICT-based systems could achieve in order to avoid this problem adapting emergency alerts and evacuation routes to different situations and people. Moreover, in order to prove the applicability of such criteria, we define a mechanism that can be used as a complement of traditional evacuation systems to provide personalized alerts and evacuation routes to all kinds of people during emergency situations in working places. This mechanism is composed by three main components: CAP-ONES for notifying emergency alerts, NERES for defining emergency plans and generating personalized evacuation routes, and iNeres as the interface to receive and visualize these routes on smartphones. The usability and understandability of proposed interface has been assessed through a user study performed in a fire simulation in an indoor environment. This evaluation demonstrated that users considered iNeres easy to understand, to learn and to use, and they also found very innovative the idea to use smartphones as a support for escaping instead of static signals on walls and doors. PMID:22969373

Cooperative vehicle routing problem: an opportunity for cost saving

NASA Astrophysics Data System (ADS)

Zibaei, Sedighe; Hafezalkotob, Ashkan; Ghashami, Seyed Sajad

2016-09-01

In this paper, a novel methodology is proposed to solve a cooperative multi-depot vehicle routing problem. We establish a mathematical model for multi-owner VRP in which each owner (i.e. player) manages single or multiple depots. The basic idea consists of offering an option that owners cooperatively manage the VRP to save their costs. We present cooperative game theory techniques for cost saving allocations which are obtained from various coalitions of owners. The methodology is illustrated with a numerical example in which different coalitions of the players are evaluated along with the results of cooperation and cost saving allocation methods.

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time

PubMed Central

Avellar, Gustavo S. C.; Pereira, Guilherme A. S.; Pimenta, Luciano C. A.; Iscold, Paulo

2015-01-01

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs. PMID:26540055

A proposal to improve e-waste collection efficiency in urban mining: Container loading and vehicle routing problems - A case study of Poland.

PubMed

Nowakowski, Piotr

2017-02-01

Waste electrical and electronic equipment (WEEE), also known as e-waste, is one of the most important waste streams with high recycling potential. Materials used in these products are valuable, but some of them are hazardous. The urban mining approach attempts to recycle as many materials as possible, so efficiency in collection is vital. There are two main methods used to collect WEEE: stationary and mobile, each with different variants. The responsibility of WEEE organizations and waste collection companies is to assure all resources required for these activities - bins, containers, collection vehicles and staff - are available, taking into account cost minimization. Therefore, it is necessary to correctly determine the capacity of containers and number of collection vehicles for an area where WEEE need to be collected. There are two main problems encountered in collection, storage and transportation of WEEE: container loading problems and vehicle routing problems. In this study, an adaptation of these two models for packing and collecting WEEE is proposed, along with a practical implementation plan designed to be useful for collection companies' guidelines for container loading and route optimization. The solutions are presented in the case studies of real-world conditions for WEEE collection companies in Poland. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of Feeder Bus Network Design and Scheduling Problems

PubMed Central

Almasi, Mohammad Hadi; Karim, Mohamed Rehan

2014-01-01

A growing concern for public transit is its inability to shift passenger's mode from private to public transport. In order to overcome this problem, a more developed feeder bus network and matched schedules will play important roles. The present paper aims to review some of the studies performed on Feeder Bus Network Design and Scheduling Problem (FNDSP) based on three distinctive parts of the FNDSP setup, namely, problem description, problem characteristics, and solution approaches. The problems consist of different subproblems including data preparation, feeder bus network design, route generation, and feeder bus scheduling. Subsequently, descriptive analysis and classification of previous works are presented to highlight the main characteristics and solution methods. Finally, some of the issues and trends for future research are identified. This paper is targeted at dealing with the FNDSP to exhibit strategic and tactical goals and also contributes to the unification of the field which might be a useful complement to the few existing reviews. PMID:24526890

Degree-constrained multicast routing for multimedia communications

NASA Astrophysics Data System (ADS)

Wang, Yanlin; Sun, Yugeng; Li, Guidan

2005-02-01

Multicast services have been increasingly used by many multimedia applications. As one of the key techniques to support multimedia applications, the rational and effective multicast routing algorithms are very important to networks performance. When switch nodes in networks have different multicast capability, multicast routing problem is modeled as the degree-constrained Steiner problem. We presented two heuristic algorithms, named BMSTA and BSPTA, for the degree-constrained case in multimedia communications. Both algorithms are used to generate degree-constrained multicast trees with bandwidth and end to end delay bound. Simulations over random networks were carried out to compare the performance of the two proposed algorithms. Experimental results show that the proposed algorithms have advantages in traffic load balancing, which can avoid link blocking and enhance networks performance efficiently. BMSTA has better ability in finding unsaturated links and (or) unsaturated nodes to generate multicast trees than BSPTA. The performance of BMSTA is affected by the variation of degree constraints.

Integrated optimization of planetary rover layout and exploration routes

NASA Astrophysics Data System (ADS)

Lee, Dongoo; Ahn, Jaemyung

2018-01-01

This article introduces an optimization framework for the integrated design of a planetary surface rover and its exploration route that is applicable to the initial phase of a planetary exploration campaign composed of multiple surface missions. The scientific capability and the mobility of a rover are modelled as functions of the science weight fraction, a key parameter characterizing the rover. The proposed problem is formulated as a mixed-integer nonlinear program that maximizes the sum of profits obtained through a planetary surface exploration mission by simultaneously determining the science weight fraction of the rover, the sites to visit and their visiting sequences under resource consumption constraints imposed on each route and collectively on a mission. A solution procedure for the proposed problem composed of two loops (the outer loop and the inner loop) is developed. The results of test cases demonstrating the effectiveness of the proposed framework are presented.

Mixed Integer Programming Model and Incremental Optimization for Delivery and Storage Planning Using Truck Terminals

NASA Astrophysics Data System (ADS)

Sakakibara, Kazutoshi; Tian, Yajie; Nishikawa, Ikuko

We discuss the planning of transportation by trucks over a multi-day period. Each truck collects loads from suppliers and delivers them to assembly plants or a truck terminal. By exploiting the truck terminal as a temporal storage, we aim to increase the load ratio of each truck and to minimize the lead time for transportation. In this paper, we show a mixed integer programming model which represents each product explicitly, and discuss the decomposition of the problem into a problem of delivery and storage, and a problem of vehicle routing. Based on this model, we propose a relax-and-fix type heuristic in which decision variables are fixed one by one by mathematical programming techniques such as branch-and-bound methods.

Harmony search optimization algorithm for a novel transportation problem in a consolidation network

NASA Astrophysics Data System (ADS)

Davod Hosseini, Seyed; Akbarpour Shirazi, Mohsen; Taghi Fatemi Ghomi, Seyed Mohammad

2014-11-01

This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.

Algorithms for Data Sharing, Coordination, and Communication in Dynamic Network Settings

DTIC Science & Technology

2007-12-03

problems in dynamic networks, focusing on mobile networks with wireless communication. Problems studied include data management, time synchronization ...The discovery of a fundamental limitation in capabilities for time synchronization in large networks. (2) The identification and development of the...Problems studied include data management, time synchronization , communication problems (broadcast, geocast, and point-to-point routing), distributed

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

PubMed

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Cognitive Task Analysis of En Route Air Traffic Control: Model Extension and Validation.

ERIC Educational Resources Information Center

Redding, Richard E.; And Others

Phase II of a project extended data collection and analytic procedures to develop a model of expertise and skill development for en route air traffic control (ATC). New data were collected by recording the Dynamic Simulator (DYSIM) performance of five experts with a work overload problem. Expert controllers were interviewed in depth for mental…

COOPERATIVE ROUTING FOR DYNAMIC AERIAL LAYER NETWORKS

DTIC Science & Technology

2018-03-01

Advisor, Computing & Communications Division Information Directorate This report is published in the interest of scientific and technical...information accumulation at the physical layer, and study the cooperative routing and resource allocation problems associated with such SU networks...interference power constraint is studied . In [Shi2012Joint], an optimal power and sub-carrier allocation strategy to maximize SUs’ throughput subject to

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

NASA Astrophysics Data System (ADS)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Automation--planning to implementation; the problems en route.

PubMed Central

Pizer, I H

1976-01-01

Once the major decision to automate library processes is made, there are a variety of problems which may be encountered before the planned system becomes operational. These include problems of personnel, budget, procurement of adjunct services, institutional priorities, and manufacturing uncertainties. Actual and potential difficulties are discussed. PMID:1247703

The production route selection algorithm in virtual manufacturing networks

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Skolud, B.; Olender, M.

2017-08-01

The increasing requirements and competition in the global market are challenges for the companies profitability in production and supply chain management. This situation became the basis for construction of virtual organizations, which are created in response to temporary needs. The problem of the production flow planning in virtual manufacturing networks is considered. In the paper the algorithm of the production route selection from the set of admissible routes, which meets the technology and resource requirements and in the context of the criterion of minimum cost is proposed.

Unstructured grids on SIMD torus machines

NASA Technical Reports Server (NTRS)

Bjorstad, Petter E.; Schreiber, Robert

1994-01-01

Unstructured grids lead to unstructured communication on distributed memory parallel computers, a problem that has been considered difficult. Here, we consider adaptive, offline communication routing for a SIMD processor grid. Our approach is empirical. We use large data sets drawn from supercomputing applications instead of an analytic model of communication load. The chief contribution of this paper is an experimental demonstration of the effectiveness of certain routing heuristics. Our routing algorithm is adaptive, nonminimal, and is generally designed to exploit locality. We have a parallel implementation of the router, and we report on its performance.

A Family of ACO Routing Protocols for Mobile Ad Hoc Networks

PubMed Central

Rupérez Cañas, Delfín; Sandoval Orozco, Ana Lucila; García Villalba, Luis Javier; Kim, Tai-hoon

2017-01-01

In this work, an ACO routing protocol for mobile ad hoc networks based on AntHocNet is specified. As its predecessor, this new protocol, called AntOR, is hybrid in the sense that it contains elements from both reactive and proactive routing. Specifically, it combines a reactive route setup process with a proactive route maintenance and improvement process. Key aspects of the AntOR protocol are the disjoint-link and disjoint-node routes, separation between the regular pheromone and the virtual pheromone in the diffusion process and the exploration of routes, taking into consideration the number of hops in the best routes. In this work, a family of ACO routing protocols based on AntOR is also specified. These protocols are based on protocol successive refinements. In this work, we also present a parallelized version of AntOR that we call PAntOR. Using programming multiprocessor architectures based on the shared memory protocol, PAntOR allows running tasks in parallel using threads. This parallelization is applicable in the route setup phase, route local repair process and link failure notification. In addition, a variant of PAntOR that consists of having more than one interface, which we call PAntOR-MI (PAntOR-Multiple Interface), is specified. This approach parallelizes the sending of broadcast messages by interface through threads. PMID:28531159

Congestion based mechanism for route discovery in a V2I-V2V system applying smart devices and IoT.

PubMed

Parrado, Natalia; Donoso, Yezid

2015-03-31

The Internet of Things is a new paradigm in which objects in a specific context can be integrated into traditional communication networks to actively participate in solving a determined problem. The Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies are specific cases of IoT and key enablers for Intelligent Transportation Systems (ITS). V2V and V2I have been widely used to solve different problems associated with transportation in cities, in which the most important is traffic congestion. A high percentage of congestion is usually presented by the inappropriate use of resources in vehicular infrastructure. In addition, the integration of traffic congestion in decision making for vehicular traffic is a challenge due to its high dynamic behavior. In this paper, an optimization model over the load balancing in the congestion percentage of the streets is formulated. Later, we explore a fully congestion-oriented route discovery mechanism and we make a proposal on the communication infrastructure that should support it based on V2I and V2V communication. The mechanism is also compared with a modified Dijkstra's approach that reacts at congestion states. Finally, we compare the results of the efficiency of the vehicle's trip with the efficiency in the use of the capacity of the vehicular network.

Congestion Based Mechanism for Route Discovery in a V2I-V2V System Applying Smart Devices and IoT

PubMed Central

Parrado, Natalia; Donoso, Yezid

2015-01-01

The Internet of Things is a new paradigm in which objects in a specific context can be integrated into traditional communication networks to actively participate in solving a determined problem. The Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies are specific cases of IoT and key enablers for Intelligent Transportation Systems (ITS). V2V and V2I have been widely used to solve different problems associated with transportation in cities, in which the most important is traffic congestion. A high percentage of congestion is usually presented by the inappropriate use of resources in vehicular infrastructure. In addition, the integration of traffic congestion in decision making for vehicular traffic is a challenge due to its high dynamic behavior. In this paper, an optimization model over the load balancing in the congestion percentage of the streets is formulated. Later, we explore a fully congestion-oriented route discovery mechanism and we make a proposal on the communication infrastructure that should support it based on V2I and V2V communication. The mechanism is also compared with a modified Dijkstra’s approach that reacts at congestion states. Finally, we compare the results of the efficiency of the vehicle’s trip with the efficiency in the use of the capacity of the vehicular network. PMID:25835185

Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks.

PubMed

Qu, Hong; Yi, Zhang; Yang, Simon X

2013-06-01

Shortest path tree (SPT) computation is a critical issue for routers using link-state routing protocols, such as the most commonly used open shortest path first and intermediate system to intermediate system. Each router needs to recompute a new SPT rooted from itself whenever a change happens in the link state. Most commercial routers do this computation by deleting the current SPT and building a new one using static algorithms such as the Dijkstra algorithm at the beginning. Such recomputation of an entire SPT is inefficient, which may consume a considerable amount of CPU time and result in a time delay in the network. Some dynamic updating methods using the information in the updated SPT have been proposed in recent years. However, there are still many limitations in those dynamic algorithms. In this paper, a new modified model of pulse-coupled neural networks (M-PCNNs) is proposed for the SPT computation. It is rigorously proved that the proposed model is capable of solving some optimization problems, such as the SPT. A static algorithm is proposed based on the M-PCNNs to compute the SPT efficiently for large-scale problems. In addition, a dynamic algorithm that makes use of the structure of the previously computed SPT is proposed, which significantly improves the efficiency of the algorithm. Simulation results demonstrate the effective and efficient performance of the proposed approach.

Exploiting Elementary Landscapes for TSP, Vehicle Routing and Scheduling

DTIC Science & Technology

2015-09-03

Traveling Salesman Problem (TSP) and Graph Coloring are elementary. Problems such as MAX-kSAT are a superposition of k elementary landscapes. This...search space. Problems such as the Traveling Salesman Problem (TSP), Graph Coloring, the Frequency Assignment Problem , as well as Min-Cut and Max-Cut...echoing our earlier esults on the Traveling Salesman Problem . Using two locally optimal solutions as “parent” solutions, we have developed a

Characterisation of an urban bus network for environmental purposes.

PubMed

André, Michel; Villanova, André

2004-12-01

Since pollutant emissions are closely related to the operating conditions of vehicles, their evaluation usually involves studying these operating conditions (through bus instrumentation and monitoring under actual operation), the design of representative driving or engine test cycles and the measurement of pollutant emissions. A preliminary characterisation of the routes on a bus network should make it possible to identify typical routes, the driving conditions and pollutant emissions of which are then studied. Two approaches are envisaged and applied to the Paris area, for which a wealth of information is available, which should be transferable to other bus networks. Both approaches are based on factorial analysis and automatic clustering, to allow optimum description and the identification of a pertinent typology of the bus routes in several classes. The first attempt at characterisation is based on statistics relating to bus operations: route characteristics (length, dedicated bus lanes, number of stops, location of stops: schools, tourist sites, hospitals, railways or underground stations), travel time, commercial speed, annual statistics (number of passengers, number of vehicles per hour, total kilometres), the irregularity of travel (variation of travel times, injuries, congestion.), as well as information on the problems encountered (congestion, distribution of the passenger load, junctions, bends). A second approach is based on the analysis of the "urban context" in which buses are driven. Population, employment, housing, road network, traffic and places that generate or disturb traffic (schools, railway stations, shopping areas, etc.) are calculated for the Ile de France region, by cells of 100 x 100 m, and collected in a geographical information system (GIS). Statistical analyses enable a typology of these urban cells to be established, the main parameters being density, type of housing, road types and traffic levels. The bus routes are then analysed according to their itineraries across these typical areas (distances travelled in each type of area) using a similar approach. A comparison of the typologies obtained from operational data and from urban data highlights the advantages and disadvantages of the two approaches. The first result from these typologies is the selection of routes which are representative of the different classes, in order to instrument buses and record driving patterns. This method should also make it possible to link driving conditions and urban characteristics, and then to allocate pollutant emission factors to given geographical situations, in particular, in the context of emission inventories or impact studies.

An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

PubMed Central

Zhang, Xuejun; Lei, Jiaxing

2015-01-01

Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

A Novel Addressing Scheme for PMIPv6 Based Global IP-WSNs

PubMed Central

Islam, Md. Motaharul; Huh, Eui-Nam

2011-01-01

IP based Wireless Sensor Networks (IP-WSNs) are being used in healthcare, home automation, industrial control and agricultural monitoring. In most of these applications global addressing of individual IP-WSN nodes and layer-three routing for mobility enabled IP-WSN with special attention to reliability, energy efficiency and end to end delay minimization are a few of the major issues to be addressed. Most of the routing protocols in WSN are based on layer-two approaches. For reliability and end to end communication enhancement the necessity of layer-three routing for IP-WSNs is generating significant attention among the research community, but due to the hurdle of maintaining routing state and other communication overhead, it was not possible to introduce a layer-three routing protocol for IP-WSNs. To address this issue we propose in this paper a global addressing scheme and layer-three based hierarchical routing protocol. The proposed addressing and routing approach focuses on all the above mentioned issues. Simulation results show that the proposed addressing and routing approach significantly enhances the reliability, energy efficiency and end to end delay minimization. We also present architecture, message formats and different routing scenarios in this paper. PMID:22164084

A novel addressing scheme for PMIPv6 based global IP-WSNs.

PubMed

Islam, Md Motaharul; Huh, Eui-Nam

2011-01-01

IP based Wireless Sensor Networks (IP-WSNs) are being used in healthcare, home automation, industrial control and agricultural monitoring. In most of these applications global addressing of individual IP-WSN nodes and layer-three routing for mobility enabled IP-WSN with special attention to reliability, energy efficiency and end to end delay minimization are a few of the major issues to be addressed. Most of the routing protocols in WSN are based on layer-two approaches. For reliability and end to end communication enhancement the necessity of layer-three routing for IP-WSNs is generating significant attention among the research community, but due to the hurdle of maintaining routing state and other communication overhead, it was not possible to introduce a layer-three routing protocol for IP-WSNs. To address this issue we propose in this paper a global addressing scheme and layer-three based hierarchical routing protocol. The proposed addressing and routing approach focuses on all the above mentioned issues. Simulation results show that the proposed addressing and routing approach significantly enhances the reliability, energy efficiency and end to end delay minimization. We also present architecture, message formats and different routing scenarios in this paper.

Intersection negotiation problems of older drivers. Volume 1

DOT National Transportation Integrated Search

1998-09-01

This project included a background literature synthesis and observational field study. The research goals were to document driving problems and errors at intersections, for older drivers using their own cars to travel familiar and unfamiliar routes, ...

A Meta-heuristic Approach for Variants of VRP in Terms of Generalized Saving Method

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki

Global logistic design is becoming a keen interest to provide an essential infrastructure associated with modern societal provision. For examples, we can designate green and/or robust logistics in transportation systems, smart grids in electricity utilization systems, and qualified service in delivery systems, and so on. As a key technology for such deployments, we engaged in practical vehicle routing problem on a basis of the conventional saving method. This paper extends such idea and gives a general framework available for various real-world applications. It can cover not only delivery problems but also two kind of pick-up problems, i.e., straight and drop-by routings. Moreover, multi-depot problem is considered by a hybrid approach with graph algorithm and its solution method is realized in a hierarchical manner. Numerical experiments have been taken place to validate effectiveness of the proposed method.

Multi-trip vehicle routing and scheduling problem with time window in real life

NASA Astrophysics Data System (ADS)

Sze, San-Nah; Chiew, Kang-Leng; Sze, Jeeu-Fong

2012-09-01

This paper studies a manpower scheduling problem with multiple maintenance operations and vehicle routing considerations. Service teams located at a common service centre are required to travel to different customer sites. All customers must be served within given time window, which are known in advance. The scheduling process must take into consideration complex constraints such as a meal break during the team's shift, multiple travelling trips, synchronisation of service teams and working shifts. The main objective of this study is to develop a heuristic that can generate high quality solution in short time for large problem instances. A Two-stage Scheduling Heuristic is developed for different variants of the problem. Empirical results show that the proposed solution performs effectively and efficiently. In addition, our proposed approximation algorithm is very flexible and can be easily adapted to different scheduling environments and operational requirements.

Fleet Assignment Using Collective Intelligence

NASA Technical Reports Server (NTRS)

Antoine, Nicolas E.; Bieniawski, Stefan R.; Kroo, Ilan M.; Wolpert, David H.

2004-01-01

Product distribution theory is a new collective intelligence-based framework for analyzing and controlling distributed systems. Its usefulness in distributed stochastic optimization is illustrated here through an airline fleet assignment problem. This problem involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of linear and non-linear constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of this new stochastic optimization algorithm to a non-linear objective cold start fleet assignment problem. Results show that the optimizer can successfully solve such highly-constrained problems (130 variables, 184 constraints).

Experimental realization of a one-way quantum computer algorithm solving Simon's problem.

PubMed

Tame, M S; Bell, B A; Di Franco, C; Wadsworth, W J; Rarity, J G

2014-11-14

We report an experimental demonstration of a one-way implementation of a quantum algorithm solving Simon's problem-a black-box period-finding problem that has an exponential gap between the classical and quantum runtime. Using an all-optical setup and modifying the bases of single-qubit measurements on a five-qubit cluster state, key representative functions of the logical two-qubit version's black box can be queried and solved. To the best of our knowledge, this work represents the first experimental realization of the quantum algorithm solving Simon's problem. The experimental results are in excellent agreement with the theoretical model, demonstrating the successful performance of the algorithm. With a view to scaling up to larger numbers of qubits, we analyze the resource requirements for an n-qubit version. This work helps highlight how one-way quantum computing provides a practical route to experimentally investigating the quantum-classical gap in the query complexity model.

Trust recovery model of Ad Hoc network based on identity authentication scheme

NASA Astrophysics Data System (ADS)

Liu, Jie; Huan, Shuiyuan

2017-05-01

Mobile Ad Hoc network trust model is widely used to solve mobile Ad Hoc network security issues. Aiming at the problem of reducing the network availability caused by the processing of malicious nodes and selfish nodes in mobile Ad Hoc network routing based on trust model, an authentication mechanism based on identity authentication mobile Ad Hoc network is proposed, which uses identity authentication to identify malicious nodes, And trust the recovery of selfish nodes in order to achieve the purpose of reducing network congestion and improving network quality. The simulation results show that the implementation of the mechanism can effectively improve the network availability and security.

Neural Network Solves "Traveling-Salesman" Problem

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.

1990-01-01

Experimental electronic neural network solves "traveling-salesman" problem. Plans round trip of minimum distance among N cities, visiting every city once and only once (without backtracking). This problem is paradigm of many problems of global optimization (e.g., routing or allocation of resources) occuring in industry, business, and government. Applied to large number of cities (or resources), circuits of this kind expected to solve problem faster and more cheaply.

Web-based routing assistance tool to reduce pavement damage by overweight and oversize vehicles.

DOT National Transportation Integrated Search

2016-10-30

This report documents the results of a completed project titled Web-Based Routing Assistance Tool to Reduce Pavement Damage by Overweight and Oversize Vehicles. The tasks involved developing a Web-based GIS routing assistance tool and evaluate ...

Assessment of Novel Routes of Biomethane Utilization in a Life Cycle Perspective

PubMed Central

Moghaddam, Elham Ahmadi; Ahlgren, Serina; Nordberg, Åke

2016-01-01

Biomethane, as a replacement for natural gas, reduces the use of fossil-based sources and supports the intended change from fossil to bio-based industry. The study assessed different biomethane utilization routes for production of methanol, dimethyl ether (DME), and ammonia, as fuel or platform chemicals and combined heat and power (CHP). Energy efficiency and environmental impacts of the different pathways was studied in a life cycle perspective covering the technical system from biomass production to the end product. Among the routes studied, CHP had the highest energy balance and least environmental impact. DME and methanol performed competently in energy balance and environmental impacts in comparison with the ammonia route. DME had the highest total energy output, as fuel, heat, and steam, among the different routes studied. Substituting the bio-based routes for fossil-based alternatives would give a considerable reduction in environmental impacts such as global warming potential and acidification potential for all routes studied, especially CHP, DME, and methanol. Eutrophication potential was mainly a result of biomass and biomethane production, with marginal differences between the different routes. PMID:28066762

Routing Based on Length of Time of Available Connection

NASA Technical Reports Server (NTRS)

Anandappan, Thanga (Inventor); Roy, Aloke (Inventor); Malve, Sharath Babu (Inventor); Toth, Louis T. (Inventor)

2016-01-01

In an embodiment, a method of routing packets at a first node in an ad-hoc network is provided. The method includes receiving, at the first node, a plurality of route-alive messages corresponding to a destination, each of the plurality of route-alive messages including a route time indicating a length of time in which a communicative connection is available between the second node that sent the respective route-alive message and the destination. The method also includes determining an updated route time for each second node. The updated route time corresponds to a length of time in which a communication connection is available between the first node and the destination through the respective second node. A second node is selected for sending a packet to based on the updated route time for each of the second nodes, wherein a node having a longer updated route time is given higher priority for selection.

Vehicle Routing with Three-dimensional Container Loading Constraints—Comparison of Nested and Joint Algorithms

NASA Astrophysics Data System (ADS)

Koloch, Grzegorz; Kaminski, Bogumil

2010-10-01

In the paper we examine a modification of the classical Vehicle Routing Problem (VRP) in which shapes of transported cargo are accounted for. This problem, known as a three-dimensional VRP with loading constraints (3D-VRP), is appropriate when transported commodities are not perfectly divisible, but they have fixed and heterogeneous dimensions. In the paper restrictions on allowable cargo positionings are also considered. These restrictions are derived from business practice and they extended the baseline 3D-VRP formulation as considered by Koloch and Kaminski (2010). In particular, we investigate how additional restrictions influence relative performance of two proposed optimization algorithms: the nested and the joint one. Performance of both methods is compared on artificial problems and on a big-scale real life case study.

Errorless-based techniques can improve route finding in early Alzheimer's disease: a case study.

PubMed

Provencher, Véronique; Bier, Nathalie; Audet, Thérèse; Gagnon, Lise

2008-01-01

Topographical disorientation is a common and early manifestation of dementia of Alzheimer type, which threatens independence in activities of daily living. Errorless-based techniques appear to be effective in helping patients with amnesia to learn routes, but little is known about their effectiveness in early dementia of Alzheimer type. A 77-year-old woman with dementia of Alzheimer type had difficulty in finding her way around her seniors residence, which reduced her social activities. This study used an ABA design (A is the baseline and B is the intervention) with multiple baselines across routes for going to the rosary (target), laundry, and game rooms (controls). The errorless-based technique intervention was applied to 2 of the 3 routes. Analyses showed significant improvement only for the routes learned with errorless-based techniques. Following the study, the participant increased her topographical knowledge of her surroundings. Route learning interventions based on errorless-based techniques appear to be a promising approach for improving the independence in early dementia of Alzheimer type.

A knowledge-based expert system for scheduling of airborne astronomical observations

NASA Technical Reports Server (NTRS)

Nachtsheim, P. R.; Gevarter, W. B.; Stutz, J. C.; Banda, C. P.

1985-01-01

The Kuiper Airborne Observatory Scheduler (KAOS) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

A Survey on Underwater Acoustic Sensor Network Routing Protocols.

PubMed

Li, Ning; Martínez, José-Fernán; Meneses Chaus, Juan Manuel; Eckert, Martina

2016-03-22

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research.

A Survey on Underwater Acoustic Sensor Network Routing Protocols

PubMed Central

Li, Ning; Martínez, José-Fernán; Meneses Chaus, Juan Manuel; Eckert, Martina

2016-01-01

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research. PMID:27011193

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

NASA Technical Reports Server (NTRS)

McNally, David; Mueller, Eric; Thipphavong, David; Paielli, Russell; Cheng, Jinn-Hwei; Lee, Chuhan; Sahlman, Scott; Walton, Joe

2010-01-01

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Brouwer, Randall Jay

1991-01-01

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization.

PubMed

Akhtar, Mahmuda; Hannan, M A; Begum, R A; Basri, Hassan; Scavino, Edgar

2017-03-01

Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO 2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO 2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Warehouse stocking optimization based on dynamic ant colony genetic algorithm

NASA Astrophysics Data System (ADS)

Xiao, Xiaoxu

2018-04-01

In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

Investigation of Simulated Trading — A multi agent based trading system for optimization purposes

NASA Astrophysics Data System (ADS)

Schneider, Johannes J.

2010-07-01

Some years ago, Bachem, Hochstättler, and Malich proposed a heuristic algorithm called Simulated Trading for the optimization of vehicle routing problems. Computational agents place buy-orders and sell-orders for customers to be handled at a virtual financial market, the prices of the orders depending on the costs of inserting the customer in the tour or for his removal. According to a proposed rule set, the financial market creates a buy-and-sell graph for the various orders in the order book, intending to optimize the overall system. Here I present a thorough investigation for the application of this algorithm to the traveling salesman problem.

Transport spatial model for the definition of green routes for city logistics centers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pamučar, Dragan, E-mail: dpamucar@gmail.com; Gigović, Ljubomir, E-mail: gigoviclj@gmail.com; Ćirović, Goran, E-mail: cirovic@sezampro.rs

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas.more » The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.« less

Optimal traffic resource allocation and management.

DOT National Transportation Integrated Search

2010-05-01

"In this paper, we address the problem of determining the patrol routes of state troopers for maximum coverage of : highway spots with high frequencies of crashes (hot spots). We develop a mixed integer linear programming model : for this problem und...

Generalized networking engineering: optimal pricing and routing in multiservice networks

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Wang, Qiong

2002-07-01

One of the functions of network engineering is to allocate resources optimally to forecasted demand. We generalize the mechanism by incorporating price-demand relationships into the problem formulation, and optimizing pricing and routing jointly to maximize total revenue. We consider a network, with fixed topology and link bandwidths, that offers multiple services, such as voice and data, each having characteristic price elasticity of demand, and quality of service and policy requirements on routing. Prices, which depend on service type and origin-destination, determine demands, that are routed, subject to their constraints, so as to maximize revenue. We study the basic properties of the optimal solution and prove that link shadow costs provide the basis for both optimal prices and optimal routing policies. We investigate the impact of input parameters, such as link capacities and price elasticities, on prices, demand growth, and routing policies. Asymptotic analyses, in which network bandwidth is scaled to grow, give results that are noteworthy for their qualitative insights. Several numerical examples illustrate the analyses.

Kleinberg Complex Networks

DTIC Science & Technology

2014-10-21

linear combinations of paths. This project featured research on two classes of routing problems , namely traveling salesman problems and multicommodity...flows. One highlight of this research was our discovery of a polynomial-time algorithm for the metric traveling salesman s-t path problem whose...metric TSP would resolve one of the most venerable open problems in the theory of approximation algorithms. Our research on traveling salesman

Route Optimization for Offloading Congested Meter Fixes

NASA Technical Reports Server (NTRS)

Xue, Min; Zelinski, Shannon

2016-01-01

The Optimized Route Capability (ORC) concept proposed by the FAA facilitates traffic managers to identify and resolve arrival flight delays caused by bottlenecks formed at arrival meter fixes when there exists imbalance between arrival fixes and runways. ORC makes use of the prediction capability of existing automation tools, monitors the traffic delays based on these predictions, and searches the best reroutes upstream of the meter fixes based on the predictions and estimated arrival schedules when delays are over a predefined threshold. Initial implementation and evaluation of the ORC concept considered only reroutes available at the time arrival congestion was first predicted. This work extends previous work by introducing an additional dimension in reroute options such that ORC can find the best time to reroute and overcome the 'firstcome- first-reroute' phenomenon. To deal with the enlarged reroute solution space, a genetic algorithm was developed to solve this problem. Experiments were conducted using the same traffic scenario used in previous work, when an arrival rush was created for one of the four arrival meter fixes at George Bush Intercontinental Houston Airport. Results showed the new approach further improved delay savings. The suggested route changes from the new approach were on average 30 minutes later than those using other approaches, and fewer numbers of reroutes were required. Fewer numbers of reroutes reduce operational complexity and later reroutes help decision makers deal with uncertain situations.

Decision-making ability of Physarum polycephalum enhanced by its coordinated spatiotemporal oscillatory dynamics.

PubMed

Iwayama, Koji; Zhu, Liping; Hirata, Yoshito; Aono, Masashi; Hara, Masahiko; Aihara, Kazuyuki

2016-04-12

An amoeboid unicellular organism, a plasmodium of the true slime mold Physarum polycephalum, exhibits complex spatiotemporal oscillatory dynamics and sophisticated information processing capabilities while deforming its amorphous body. We previously devised an 'amoeba-based computer (ABC),' that implemented optical feedback control to lead this amoeboid organism to search for a solution to the traveling salesman problem (TSP). In the ABC, the shortest TSP route (the optimal solution) is represented by the shape of the organism in which the body area (nutrient absorption) is maximized while the risk of being exposed to aversive light stimuli is minimized. The shortness of the TSP route found by ABC, therefore, serves as a quantitative measure of the optimality of the decision made by the organism. However, it remains unclear how the decision-making ability of the organism originates from the oscillatory dynamics of the organism. We investigated the number of coexisting traveling waves in the spatiotemporal patterns of the oscillatory dynamics of the organism. We show that a shorter TSP route can be found when the organism exhibits a lower number of traveling waves. The results imply that the oscillatory dynamics are highly coordinated throughout the global body. Based on the results, we discuss the fact that the decision-making ability of the organism can be enhanced not by uncorrelated random fluctuations, but by its highly coordinated oscillatory dynamics.

Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy.

PubMed

Xing, KeYi; Han, LiBin; Zhou, MengChu; Wang, Feng

2012-06-01

Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.

Energy consumption and control response evaluations of AODV routing in WSANs for building-temperature control.

PubMed

Booranawong, Apidet; Teerapabkajorndet, Wiklom; Limsakul, Chusak

2013-06-27

The main objective of this paper is to investigate the effects of routing protocols on wireless sensor and actuator networks (WSANs), focusing on the control system response and the energy consumption of nodes in a network. We demonstrate that routing algorithms designed without considering the relationship between communication and control cannot be appropriately used in wireless networked control applications. For this purpose, an ad-hoc on-demand distance vector (AODV) routing, an IEEE 802.15.4, and a building-temperature control system are employed for this exploration. The findings from our scenarios show that the AODV routing can select a path with a high traffic load for data transmission. It takes a long time before deciding to change a new route although it experiences the unsuccessful transmission of packets. As a result, the desirable control target cannot be achieved in time, and nodes consume more energy due to frequent packet collisions and retransmissions. Consequently, we propose a simple routing solution to alleviate these research problems by modifying the original AODV routing protocol. The delay-threshold is considered to avoid any congested connection during routing procedures. The simulation results demonstrate that our solution can be appropriately applied in WSANs. Both the energy consumption and the control system response are improved.