Coordinating, Scheduling, Processing and Analyzing IYA09
NASA Technical Reports Server (NTRS)
Gipson, John; Behrend, Dirk; Gordon, David; Himwich, Ed; MacMillan, Dan; Titus, Mike; Corey, Brian
2010-01-01
The IVS scheduled a special astrometric VLBI session for the International Year of Astronomy 2009 (IYA09) commemorating 400 years of optical astronomy and 40 years of VLBI. The IYA09 session is the most ambitious geodetic session to date in terms of network size, number of sources, and number of observations. We describe the process of designing, coordinating, scheduling, pre-session station checkout, correlating, and analyzing this session.
The Microchp Scheduling Problem
NASA Astrophysics Data System (ADS)
Bosman, M. G. C.; Bakker, V.; Molderink, A.; Hurink, J. L.; Smit, G. J. M.
2009-08-01
The increasing penetration of renewable energy sources, the demand for more energy efficient electricity production and the increase in distributed electricity generation causes a shift in the way electricity is produced and consumed. The downside of these changes in the electricity grid is that network stability and controllability becomes more difficult compared to the old situation. The new network has to accommodate various means of production, consumption and buffering and needs to offer control over the energy flows between these three elements. In order to offer such a control mechanism we need to know more about the individual aspects. In this paper we focus on the modelling of distributed production. Especially we look at the use of microCHP (Combined Heat and Power) appliances in a group of houses. The problem of planning the production runs of the microCHP is modelled via an ILP formulation both for a single house and for a group of houses.
Coordinated Science Campaign Scheduling for Sensor Webs
NASA Technical Reports Server (NTRS)
Edgington, Will; Morris, Robert; Dungan, Jennifer; Williams, Jenny; Carlson, Jean; Fleming, Damian; Wood, Terri; Yorke-Smith, Neil
2005-01-01
Future Earth observing missions will study different aspects and interacting pieces of the Earth's eco-system. Scientists are designing increasingly complex, interdisciplinary campaigns to exploit the diverse capabilities of multiple Earth sensing assets. In addition, spacecraft platforms are being configured into clusters, trains, or other distributed organizations in order to improve either the quality or the coverage of observations. These simultaneous advances in the design of science campaigns and in the missions that will provide the sensing resources to support them offer new challenges in the coordination of data and operations that are not addressed by current practice. For example, the scheduling of scientific observations for satellites in low Earth orbit is currently conducted independently by each mission operations center. An absence of an information infrastructure to enable the scheduling of coordinated observations involving multiple sensors makes it difficult to execute campaigns involving multiple assets. This paper proposes a software architecture and describes a prototype system called DESOPS (Distributed Earth Science Observation Planning and Scheduling) that will address this deficiency.
32 CFR 644.395 - Coordination on disposal problems.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 32 National Defense 4 2010-07-01 2010-07-01 true Coordination on disposal problems. 644.395... PROPERTY REAL ESTATE HANDBOOK Disposal Predisposal Action § 644.395 Coordination on disposal problems. If any major change or problem requires a significant revision in the time schedule for disposal,...
32 CFR 644.395 - Coordination on disposal problems.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 32 National Defense 4 2011-07-01 2011-07-01 false Coordination on disposal problems. 644.395... PROPERTY REAL ESTATE HANDBOOK Disposal Predisposal Action § 644.395 Coordination on disposal problems. If any major change or problem requires a significant revision in the time schedule for disposal,...
Integrated network design and scheduling problems :
Nurre, Sarah G.; Carlson, Jeffrey J.
2014-01-01
We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.
Group scheduling problems in directional sensor networks
NASA Astrophysics Data System (ADS)
Singh, Alok; Rossi, André
2015-12-01
This article addresses the problem of scheduling a set of groups of directional sensors arising as a result of applying an exact or a heuristic approach for solving a problem involving directional sensors. The problem seeks a schedule for these groups that minimizes the total energy consumed in switching from one group to the next group in the schedule. In practice, when switching from a group to the next one, active sensors in the new group have to rotate in order to face their working direction. These rotations consume energy, and the problem is to schedule the groups so as to minimize the total amount of energy consumed by all the sensor rotations, knowing the initial angular positions of all the sensors. In this article, it is assumed that energy consumption is proportional to the angular movement for all the sensors. Another problem version is also investigated that seeks to minimize the total time during which the sensor network cannot cover all the targets because active sensors are rotating. Both problems are proved to be ?-hard, and a lower bound for the first problem is presented. A greedy heuristic and a genetic algorithm are also proposed for addressing the problem of minimizing total rotation in the general case. Finally, a local search is also proposed to improve the solutions obtained through a genetic algorithm.
Fuzzy coordinator in control problems
NASA Technical Reports Server (NTRS)
Rueda, A.; Pedrycz, W.
1992-01-01
In this paper a hierarchical control structure using a fuzzy system for coordination of the control actions is studied. The architecture involves two levels of control: a coordination level and an execution level. Numerical experiments will be utilized to illustrate the behavior of the controller when it is applied to a nonlinear plant.
Coordinated Transportation: Problems and Promise?
ERIC Educational Resources Information Center
Fickes, Michael
1998-01-01
Examines the legal, administrative, and logistical barriers that have prevented the wide acceptance of coordinating community and school transportation services and why these barriers may be breaking down. Two examples of successful implementation of coordinated transportation are examined: employing a single system to serve all transportation…
Separation Assurance and Scheduling Coordination in the Arrival Environment
NASA Technical Reports Server (NTRS)
Aweiss, Arwa S.; Cone, Andrew C.; Holladay, Joshua J.; Munoz, Epifanio; Lewis, Timothy A.
2016-01-01
Separation assurance (SA) automation has been proposed as either a ground-based or airborne paradigm. The arrival environment is complex because aircraft are being sequenced and spaced to the arrival fix. This paper examines the effect of the allocation of the SA and scheduling functions on the performance of the system. Two coordination configurations between an SA and an arrival management system are tested using both ground and airborne implementations. All configurations have a conflict detection and resolution (CD&R) system and either an integrated or separated scheduler. Performance metrics are presented for the ground and airborne systems based on arrival traffic headed to Dallas/ Fort Worth International airport. The total delay, time-spacing conformance, and schedule conformance are used to measure efficiency. The goal of the analysis is to use the metrics to identify performance differences between the configurations that are based on different function allocations. A surveillance range limitation of 100 nmi and a time delay for sharing updated trajectory intent of 30 seconds were implemented for the airborne system. Overall, these results indicate that the surveillance range and the sharing of trajectories and aircraft schedules are important factors in determining the efficiency of an airborne arrival management system. These parameters are not relevant to the ground-based system as modeled for this study because it has instantaneous access to all aircraft trajectories and intent. Creating a schedule external to the CD&R and the scheduling conformance system was seen to reduce total delays for the airborne system, and had a minor effect on the ground-based system. The effect of an external scheduler on other metrics was mixed.
Optimal pre-scheduling of problem remappings
NASA Technical Reports Server (NTRS)
Nicol, David M.; Saltz, Joel H.
1987-01-01
A large class of scientific computational problems can be characterized as a sequence of steps where a significant amount of computation occurs each step, but the work performed at each step is not necessarily identical. Two good examples of this type of computation are: (1) regridding methods which change the problem discretization during the course of the computation, and (2) methods for solving sparse triangular systems of linear equations. Recent work has investigated a means of mapping such computations onto parallel processors; the method defines a family of static mappings with differing degrees of importance placed on the conflicting goals of good load balance and low communication/synchronization overhead. The performance tradeoffs are controllable by adjusting the parameters of the mapping method. To achieve good performance it may be necessary to dynamically change these parameters at run-time, but such changes can impose additional costs. If the computation's behavior can be determined prior to its execution, it can be possible to construct an optimal parameter schedule using a low-order-polynomial-time dynamic programming algorithm. Since the latter can be expensive, the performance is studied of the effect of a linear-time scheduling heuristic on one of the model problems, and it is shown to be effective and nearly optimal.
Coordinated scheduling for dynamic real-time systems
NASA Technical Reports Server (NTRS)
Natarajan, Swaminathan; Zhao, Wei
1994-01-01
In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.
Optimizing Center Performance through Coordinated Data Staging, Scheduling and Recovery
Zhang, Zhe; Wang, Chao; Vazhkudai, Sudharshan S; Ma, Xiaosong; Pike, Gregory; Cobb, John W; Mueller, Frank
2007-01-01
Procurement and optimized utilization of Petascale supercomputers and centers is a renewed national priority. Sustained performance and availability of such large centers is a key technical challenge significantly impacting their usability. As recent research shows, storage systems can be a primary fault source leading to unavailability of even today's supercomputer. Due to data unavailability, jobs are frequently resubmitted resulting in reduced compute center performance as well as in a lack of coordination between I/O activities and job scheduling. In this work, we explore two mechanisms, namely the coordination of job scheduling and data staging/offloading and on-demand job input data reconstruction to address the availability of job input/output data and to improve center-wide performance. Fundamental to both mechanisms is the efficient management of transient data: in the way it is scheduled and recovered. Collectively, from a center standpoint, these techniques optimize resource usage and increase its data/service availability. From a user job standpoint, they reduce job turnaround time and optimize the usage of allocated time. We have implemented our approaches within commonly used supercomputer software tools such as the PBS scheduler and the Lustre parallel file system. We have gathered reconstruction data from a production supercomputer environment using multiple data sources. We conducted simulations based on the measured data recovery performance, the job traces and staged data logs from leadership-class supercomputer centers. Our results indicate that the average waiting time of jobs is reduced. This trend increases significantly for larger jobs and also as data is striped over more I/O nodes.
NASA Technical Reports Server (NTRS)
Moore, J. E.
1975-01-01
An enumeration algorithm is presented for solving a scheduling problem similar to the single machine job shop problem with sequence dependent setup times. The scheduling problem differs from the job shop problem in two ways. First, its objective is to select an optimum subset of the available tasks to be performed during a fixed period of time. Secondly, each task scheduled is constrained to occur within its particular scheduling window. The algorithm is currently being used to develop typical observational timelines for a telescope that will be operated in earth orbit. Computational times associated with timeline development are presented.
48 CFR 536.570-9 - Shop drawings, coordination drawings, and schedules.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false Shop drawings, coordination drawings, and schedules. 536.570-9 Section 536.570-9 Federal Acquisition Regulations System... CONTRACTS Contract Clauses 536.570-9 Shop drawings, coordination drawings, and schedules. Insert the...
48 CFR 536.570-9 - Shop drawings, coordination drawings, and schedules.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false Shop drawings, coordination drawings, and schedules. 536.570-9 Section 536.570-9 Federal Acquisition Regulations System... CONTRACTS Contract Clauses 536.570-9 Shop drawings, coordination drawings, and schedules. Insert the...
48 CFR 552.236-78 - Shop Drawings, Coordination Drawings, and Schedules.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Shop Drawings, Coordination Drawings, and Schedules. 552.236-78 Section 552.236-78 Federal Acquisition Regulations System... Provisions and Clauses 552.236-78 Shop Drawings, Coordination Drawings, and Schedules. As prescribed in...
48 CFR 552.236-78 - Shop Drawings, Coordination Drawings, and Schedules.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false Shop Drawings, Coordination Drawings, and Schedules. 552.236-78 Section 552.236-78 Federal Acquisition Regulations System... Provisions and Clauses 552.236-78 Shop Drawings, Coordination Drawings, and Schedules. As prescribed in...
48 CFR 536.570-9 - Shop drawings, coordination drawings, and schedules.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Shop drawings, coordination drawings, and schedules. 536.570-9 Section 536.570-9 Federal Acquisition Regulations System... CONTRACTS Contract Clauses 536.570-9 Shop drawings, coordination drawings, and schedules. Insert the...
48 CFR 552.236-78 - Shop Drawings, Coordination Drawings, and Schedules.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false Shop Drawings, Coordination Drawings, and Schedules. 552.236-78 Section 552.236-78 Federal Acquisition Regulations System... Provisions and Clauses 552.236-78 Shop Drawings, Coordination Drawings, and Schedules. As prescribed in...
48 CFR 536.570-9 - Shop drawings, coordination drawings, and schedules.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Shop drawings, coordination drawings, and schedules. 536.570-9 Section 536.570-9 Federal Acquisition Regulations System... CONTRACTS Contract Clauses 536.570-9 Shop drawings, coordination drawings, and schedules. Insert the...
Job shop scheduling problem with late work criterion
NASA Astrophysics Data System (ADS)
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.
AI techniques for a space application scheduling problem
NASA Technical Reports Server (NTRS)
Thalman, N.; Sparn, T.; Jaffres, L.; Gablehouse, D.; Judd, D.; Russell, C.
1991-01-01
Scheduling is a very complex optimization problem which can be categorized as an NP-complete problem. NP-complete problems are quite diverse, as are the algorithms used in searching for an optimal solution. In most cases, the best solutions that can be derived for these combinatorial explosive problems are near-optimal solutions. Due to the complexity of the scheduling problem, artificial intelligence (AI) can aid in solving these types of problems. Some of the factors are examined which make space application scheduling problems difficult and presents a fairly new AI-based technique called tabu search as applied to a real scheduling application. the specific problem is concerned with scheduling application. The specific problem is concerned with scheduling solar and stellar observations for the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) instrument in a constrained environment which produces minimum impact on the other instruments and maximizes target observation times. The SOLSTICE instrument will gly on-board the Upper Atmosphere Research Satellite (UARS) in 1991, and a similar instrument will fly on the earth observing system (Eos).
Handling Deafness Problem of Scheduled Multi-Channel Polling MACs
NASA Astrophysics Data System (ADS)
Jiang, Fulong; Liu, Hao; Shi, Longxing
Combining scheduled channel polling with channel diversity is a promising way for a MAC protocol to achieve high energy efficiency and performance under both light and heavy traffic conditions. However, the deafness problem may cancel out the benefit of channel diversity. In this paper, we first investigate the deafness problem of scheduled multi-channel polling MACs with experiments. Then we propose and evaluate two schemes to handle the deafness problem. Our experiment shows that deafness is a significant reason for performance degradation in scheduled multi-channel polling MACs. A proper scheme should be chosen depending on the traffic pattern and the design objective.
The application of artificial intelligence to astronomical scheduling problems
NASA Technical Reports Server (NTRS)
Johnston, Mark D.
1992-01-01
Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike
Analysis of Feeder Bus Network Design and Scheduling Problems
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
NASA Astrophysics Data System (ADS)
Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying
Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.
Coordinating space telescope operations in an integrated planning and scheduling architecture
NASA Technical Reports Server (NTRS)
Muscettola, Nicola; Smith, Stephen F.; Cesta, Amedeo; D'Aloisi, Daniela
1992-01-01
The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.
Innately Split Model for Job-shop Scheduling Problem
NASA Astrophysics Data System (ADS)
Ikeda, Kokolo; Kobayashi, Sigenobu
Job-shop Scheduling Problem (JSP) is one of the most difficult benchmark problems. GA approaches often fail searching the global optimum because of the deception UV-structure of JSPs. In this paper, we introduce a novel framework model of GA, Innately Split Model (ISM) which prevents UV-phenomenon, and discuss on its power particularly. Next we analyze the structure of JSPs with the help of the UV-structure hypothesys, and finally we show ISM's excellent performance on JSP.
NASA Astrophysics Data System (ADS)
Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki
This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.
Extended precedence preservative crossover for job shop scheduling problems
NASA Astrophysics Data System (ADS)
Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd
2013-04-01
Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.
Solving Open Job-Shop Scheduling Problems by SAT Encoding
NASA Astrophysics Data System (ADS)
Koshimura, Miyuki; Nabeshima, Hidetomo; Fujita, Hiroshi; Hasegawa, Ryuzo
This paper tries to solve open Job-Shop Scheduling Problems (JSSP) by translating them into Boolean Satisfiability Testing Problems (SAT). The encoding method is essentially the same as the one proposed by Crawford and Baker. The open problems are ABZ8, ABZ9, YN1, YN2, YN3, and YN4. We proved that the best known upper bounds 678 of ABZ9 and 884 of YN1 are indeed optimal. We also improved the upper bound of YN2 and lower bounds of ABZ8, YN2, YN3 and YN4.
A Heuristic Approach for International Crude Oil Transportation Scheduling Problems
NASA Astrophysics Data System (ADS)
Yin, Sisi; Nishi, Tatsushi; Izuno, Tsukasa
In this paper, we propose a heuristic algorithm to solve a practical ship scheduling problem for international crude oil transportation. The problem is considered as a vehicle routing problem with split deliveries. The objective of this paper is to find an optimal assignment of tankers, a sequence of visiting and loading volume simultaneously in order to minimize the total distance satisfying the capacity of tankers. A savings-based meta-heuristic algorithm with lot sizing parameters and volume assignment heuristic is developed. The proposed method is applied to solve a case study with real data. Computational results demonstrate the effectiveness of the heuristic algorithm compared with that of human operators.
Artificial immune algorithm for multi-depot vehicle scheduling problems
NASA Astrophysics Data System (ADS)
Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling
2008-10-01
In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.
Children Use Salience to Solve Coordination Problems
ERIC Educational Resources Information Center
Grueneisen, Sebastian; Wyman, Emily; Tomasello, Michael
2015-01-01
Humans are routinely required to coordinate with others. When communication is not possible, adults often achieve this by using salient cues in the environment (e.g. going to the Eiffel Tower, as an obvious meeting point). To explore the development of this capacity, we presented dyads of 3-, 5-, and 8-year-olds (N = 144) with a coordination…
Automated problem scheduling and reduction of synchronization delay effects
NASA Technical Reports Server (NTRS)
Saltz, Joel H.
1987-01-01
It is anticipated that in order to make effective use of many future high performance architectures, programs will have to exhibit at least a medium grained parallelism. A framework is presented for partitioning very sparse triangular systems of linear equations that is designed to produce favorable preformance results in a wide variety of parallel architectures. Efficient methods for solving these systems are of interest because: (1) they provide a useful model problem for use in exploring heuristics for the aggregation, mapping and scheduling of relatively fine grained computations whose data dependencies are specified by directed acrylic graphs, and (2) because such efficient methods can find direct application in the development of parallel algorithms for scientific computation. Simple expressions are derived that describe how to schedule computational work with varying degrees of granularity. The Encore Multimax was used as a hardware simulator to investigate the performance effects of using the partitioning techniques presented in shared memory architectures with varying relative synchronization costs.
An Improved Differential Evolution Solution for Software Project Scheduling Problem
Biju, A. C.; Victoire, T. Aruldoss Albert; Mohanasundaram, Kumaresan
2015-01-01
This paper proposes a differential evolution (DE) method for the software project scheduling problem (SPSP). The interest on finding a more efficient solution technique for SPSP is always a topic of interest due to the fact of ever growing challenges faced by the software industry. The curse of dimensionality is introduced in the scheduling problem by ever increasing software assignments and the number of staff who handles it. Thus the SPSP is a class of NP-hard problem, which requires a rigorous solution procedure which guarantees a reasonably better solution. Differential evolution is a direct search stochastic optimization technique that is fairly fast and reasonably robust. It is also capable of handling nondifferentiable, nonlinear, and multimodal objective functions like SPSP. This paper proposes a refined DE where a new mutation mechanism is introduced. The superiority of the proposed method is experimented and demonstrated by solving the SPSP on 50 random instances and the results are compared with some of the techniques in the literature. PMID:26495419
Petri Net Modeling and Decomposition Method for Solving Production Scheduling Problems
NASA Astrophysics Data System (ADS)
Nishi, Tatsushi; Maeno, Ryota
Considering the need to develop general scheduling problem solver, the recent integration of Petri Nets as modeling tools into effective optimization methods for scheduling problems is very promising. The paper addresses a Petri Net modeling and decomposition method for solving a wide variety of scheduling problems. The scheduling problems are represented as the optimal transition firing sequence problems for timed Petri Nets. The Petri Net is decomposed into several subnets in which each subproblem can be easily solved by Dijkstra' algorithm. The approach is applied to a flowshop scheduling problem. The performance of the proposed algorithm is compared with that of a simulated annealing method.
Walking (Gait), Balance, and Coordination Problems
... tizanidine are generally effective in treating this symptom. Balance : Balance problems typically result in a swaying and “drunken” ... factors for falls are complex and include: poor balance and slowed walking reduced proprioception (the sensation of ...
Applications of dynamic scheduling technique to space related problems: Some case studies
NASA Technical Reports Server (NTRS)
Nakasuka, Shinichi; Ninomiya, Tetsujiro
1994-01-01
The paper discusses the applications of 'Dynamic Scheduling' technique, which has been invented for the scheduling of Flexible Manufacturing System, to two space related scheduling problems: operation scheduling of a future space transportation system, and resource allocation in a space system with limited resources such as space station or space shuttle.
Applications of dynamic scheduling technique to space related problems: Some case studies
NASA Astrophysics Data System (ADS)
Nakasuka, Shinichi; Ninomiya, Tetsujiro
1994-10-01
The paper discusses the applications of 'Dynamic Scheduling' technique, which has been invented for the scheduling of Flexible Manufacturing System, to two space related scheduling problems: operation scheduling of a future space transportation system, and resource allocation in a space system with limited resources such as space station or space shuttle.
JIT single machine scheduling problem with periodic preventive maintenance
NASA Astrophysics Data System (ADS)
Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani
2016-03-01
This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms.
Mathematical Problems in Children with Developmental Coordination Disorder
ERIC Educational Resources Information Center
Pieters, Stefanie; Desoete, Annemie; Van Waelvelde, Hilde; Vanderswalmen, Ruth; Roeyers, Herbert
2012-01-01
Developmental coordination disorder (DCD) is a heterogeneous disorder, which is often co-morbid with learning disabilities. However, mathematical problems have rarely been studied in DCD. The aim of this study was to investigate the mathematical problems in children with various degrees of motor problems. Specifically, this study explored if the…
Nurse Scheduling System based on Dynamic Weighted Maximal Constraint Satisfaction Problem
NASA Astrophysics Data System (ADS)
Hattori, Hiromitsu; Isomura, Atsushi; Ito, Takayuki; Ozono, Tadachika; Shintani, Toramatsu
Scheduling has been an important research field in Artificial Intelligence. Because typical scheduling problems could be modeled as a Constraint Satisfaction Problem(CSP), several constraint satisfaction techniques have been proposed. In order to handle the different levels of importance of the constraints, solving a problem as a Weighted Maximal Constraint Satisfaction Problem(W-MaxCSP) is an promising approach. However, there exists the case where unexpected events are added and some sudden changes are required, i.e., the case with dynamic changes in scheduling problems. In this paper, we describe such dynamic scheduling problem as a Dynamic Weighted Maximal Constraint Satisfaction Problem(DW-MaxCSP) in which constraints would changes dynamically. Generally, it is undesirable to determine vastly modified schedule even if re-scheduling is needed. A new schedule should be close to the current one as much as possible. In order to obtain stable solutions, we propose the methodology to maintain portions of the current schedule using the provisional soft constraints, which explicitly penalize the changes from the current schedule. We have experimentally confirmed the efficacy of re-scheduling based on our method with provisional constraints. In this paper, we construct the nurse scheduling system for applying the proposed scheduling method.
Genetic-Annealing Algorithm in Grid Environment for Scheduling Problems
NASA Astrophysics Data System (ADS)
Cruz-Chávez, Marco Antonio; Rodríguez-León, Abelardo; Ávila-Melgar, Erika Yesenia; Juárez-Pérez, Fredy; Cruz-Rosales, Martín H.; Rivera-López, Rafael
This paper presents a parallel hybrid evolutionary algorithm executed in a grid environment. The algorithm executes local searches using simulated annealing within a Genetic Algorithm to solve the job shop scheduling problem. Experimental results of the algorithm obtained in the "Tarantula MiniGrid" are shown. Tarantula was implemented by linking two clusters from different geographic locations in Mexico (Morelos-Veracruz). The technique used to link the two clusters and configure the Tarantula MiniGrid is described. The effects of latency in communication between the two clusters are discussed. It is shown that the evolutionary algorithm presented is more efficient working in Grid environments because it can carry out major exploration and exploitation of the solution space.
A coordinated approach for real-time short term hydro scheduling
Tufegdzic, N.; Frowd, R.J.; Stadlin, W.O.
1996-11-01
The paper describes a coordinated approach to short-term hydro scheduling and dispatch that has been developed as a part of the Tasmanian Hydro Electric Commission`s (HEC) new Energy Management System (EMS), which is being delivered by Landis and Gyr Energy Management. Tasmania`s hydro generation system consists of 40 reservoirs in six river catchments. The daily water release for each plant is scheduled using the HEC`s mid-term operation policy. The Hydro Scheduling and Commitment (HSC) function schedules the hydro units on a half hourly basis so that the allocated water release maximizes the energy production. This maximization of energy production is achieved by maximizing the head and this ensures that operation is always as close as possible to maximum efficiency. Mixed Integer Linear Programming is used with a detailed model of the interconnected hydro system to determine the half-hourly operation schedule. The Hydro Economic Dispatch (HED) function is used to implement the schedules produced by HSC in the real-time operation. The HED also uses a detailed model of the hydro system with a Linear Programming algorithm to ensure that each unit operates as close as possible to its head-dependent theoretical maximum efficiency point while meeting the desired storage levels specified by the HSC solution. HSC and HED have been tested against a number of operational scenarios and when it is fully integrated within the new EMS it is expected to yield annual stored energy savings up to 0.5% through more efficient hydro-electric system operation. It is expected to also provide additional savings by fostering improvements to the mid-term operating plan.
NASA Technical Reports Server (NTRS)
Smith, Stephen F.; Pathak, Dhiraj K.
1991-01-01
In this paper, we report work aimed at applying concepts of constraint-based problem structuring and multi-perspective scheduling to an over-subscribed scheduling problem. Previous research has demonstrated the utility of these concepts as a means for effectively balancing conflicting objectives in constraint-relaxable scheduling problems, and our goal here is to provide evidence of their similar potential in the context of HST observation scheduling. To this end, we define and experimentally assess the performance of two time-bounded heuristic scheduling strategies in balancing the tradeoff between resource setup time minimization and satisfaction of absolute time constraints. The first strategy considered is motivated by dispatch-based manufacturing scheduling research, and employs a problem decomposition that concentrates local search on minimizing resource idle time due to setup activities. The second is motivated by research in opportunistic scheduling and advocates a problem decomposition that focuses attention on the goal activities that have the tightest temporal constraints. Analysis of experimental results gives evidence of differential superiority on the part of each strategy in different problem solving circumstances. A composite strategy based on recognition of characteristics of the current problem solving state is then defined and tested to illustrate the potential benefits of constraint-based problem structuring and multi-perspective scheduling in over-subscribe scheduling problems.
Training State Child Service Coordinators in Creative Problem Solving.
ERIC Educational Resources Information Center
Combs, Wendy LeeAnn; Gilman, David Alan
The preliminary findings of the evaluation of the training program, Creative Problem Solving, are presented. The training was provided through the Blumberg Center for Interdisciplinary Studies in Special Education at Indiana State University. Twenty-one state and county child service coordinators participated in the training on a voluntary basis.…
Spreading order: religion, cooperative niche construction, and risky coordination problems.
Bulbulia, Joseph
2012-01-01
Adaptationists explain the evolution of religion from the cooperative effects of religious commitments, but which cooperation problem does religion evolve to solve? I focus on a class of symmetrical coordination problems for which there are two pure Nash equilibriums: (1) ALL COOPERATE, which is efficient but relies on full cooperation; (2) ALL DEFECT, which is inefficient but pays regardless of what others choose. Formal and experimental studies reveal that for such risky coordination problems, only the defection equilibrium is evolutionarily stable. The following makes sense of otherwise puzzling properties of religious cognition and cultures as features of cooperative designs that evolve to stabilise such risky exchange. The model is interesting because it explains lingering puzzles in the data on religion, and better integrates evolutionary theories of religion with recent, well-motivated models of cooperative niche construction. PMID:22207773
Coordinating complex problem-solving among distributed intelligent agents
NASA Technical Reports Server (NTRS)
Adler, Richard M.
1992-01-01
A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220
Protocols for distributive scheduling
NASA Technical Reports Server (NTRS)
Richards, Stephen F.; Fox, Barry
1993-01-01
The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of space shuttle mission planning.
Coordinated problem solving through resource sharing in a distributed environment.
Deshpande, Umesh; Gupta, Arobinda; Basu, Anupam
2004-04-01
An important feature in a distributed problem solving system is that the resources of different nodes can be shared through cooperation. In this paper, the generalized partial global planning (GPGP) approach used for multiagent systems is extended by providing a coordination mechanism for resource sharing across nodes. In our framework, multiple conflicting criteria (or objectives) like quality, cost, and duration may be associated with an input task. Preference ratings expressed subjectively may be assigned to each of the criteria. Task assignment in this system, which is a multiobjective decision making problem, is important for the satisfaction of the criteria. It has to be done with imprecise information since the system is dynamic and preference ratings are specified subjectively. A technique for task assignment using the fuzzy set approach is also presented in this paper. Simulation studies for the coordination mechanism and the task assignment have been performed to demonstrate their effectiveness. PMID:15376875
Children's capacity to use cultural focal points in coordination problems.
Goldvicht-Bacon, Efrat; Diesendruck, Gil
2016-04-01
Coordination problems require one to act based on expectations about how partners will act. In Experiment 1, 5-year-olds (n=57) had to hide a sticker in the box another child from their, or a different, culture was most likely to search in. Boxes were marked with cues presumed to be known by everybody, cultural members, or the child. Experiment 2 assessed 5-year-olds' (n=57) behavior in a competition scenario. In Experiment 1, children were more likely to hide in the cultural box when playing with a same- than a different-culture partner. In Experiment 2, children's behavior was the opposite. Thus by age 5, children are capable of modulating their actions in coordination problems, according to their partners' presumed knowledge. PMID:26826539
Parallel-Batch Scheduling and Transportation Coordination with Waiting Time Constraint
Gong, Hua; Chen, Daheng; Xu, Ke
2014-01-01
This paper addresses a parallel-batch scheduling problem that incorporates transportation of raw materials or semifinished products before processing with waiting time constraint. The orders located at the different suppliers are transported by some vehicles to a manufacturing facility for further processing. One vehicle can load only one order in one shipment. Each order arriving at the facility must be processed in the limited waiting time. The orders are processed in batches on a parallel-batch machine, where a batch contains several orders and the processing time of the batch is the largest processing time of the orders in it. The goal is to find a schedule to minimize the sum of the total flow time and the production cost. We prove that the general problem is NP-hard in the strong sense. We also demonstrate that the problem with equal processing times on the machine is NP-hard. Furthermore, a dynamic programming algorithm in pseudopolynomial time is provided to prove its ordinarily NP-hardness. An optimal algorithm in polynomial time is presented to solve a special case with equal processing times and equal transportation times for each order. PMID:24883385
An Optimization Model for Scheduling Problems with Two-Dimensional Spatial Resource Constraint
NASA Technical Reports Server (NTRS)
Garcia, Christopher; Rabadi, Ghaith
2010-01-01
Traditional scheduling problems involve determining temporal assignments for a set of jobs in order to optimize some objective. Some scheduling problems also require the use of limited resources, which adds another dimension of complexity. In this paper we introduce a spatial resource-constrained scheduling problem that can arise in assembly, warehousing, cross-docking, inventory management, and other areas of logistics and supply chain management. This scheduling problem involves a twodimensional rectangular area as a limited resource. Each job, in addition to having temporal requirements, has a width and a height and utilizes a certain amount of space inside the area. We propose an optimization model for scheduling the jobs while respecting all temporal and spatial constraints.
What Causes Care Coordination Problems? A Case for Microanalysis
Zachary, Wayne; Maulitz, Russell Charles; Zachary, Drew A.
2016-01-01
Introduction: Care coordination (CC) is an important fulcrum for pursuing a range of health care goals. Current research and policy analyses have focused on aggregated data rather than on understanding what happens within individual cases. At the case level, CC emerges as a complex network of communications among providers over time, crossing and recrossing many organizational boundaries. Micro-level analysis is needed to understand where and how CC fails, as well as to identify best practices and root causes of problems. Coordination Process Diagramming: Coordination Process Diagramming (CPD) is a new framework for representing and analyzing CC arcs at the micro level, separating an arc into its participants and roles, communication structure, organizational structures, and transitions of care, all on a common time line. Conclusion: Comparative CPD analysis across a sample of CC arcs identifies common CC problems and potential root causes, showing the potential value of the framework. The analyses also suggest intervention strategies that could be applied to attack the root causes of CC problems, including organizational changes, education and training, and additional health information technology development. PMID:27563685
Optimizing scheduling problem using an estimation of distribution algorithm and genetic algorithm
NASA Astrophysics Data System (ADS)
Qun, Jiang; Yang, Ou; Dong, Shi-Du
2007-12-01
This paper presents a methodology for using heuristic search methods to optimize scheduling problem. Specifically, an Estimation of Distribution Algorithm (EDA)- Population Based Incremental Learning (PBIL), and Genetic Algorithm (GA) have been applied to finding effective arrangement of curriculum schedule of Universities. To our knowledge, EDAs have been applied to fewer real world problems compared to GAs, and the goal of the present paper is to expand the application domain of this technique. The experimental results indicate a good applicability of PBIL to optimize scheduling problem.
The problem of scheduling for the linear section of a single-track railway
NASA Astrophysics Data System (ADS)
Akimova, Elena N.; Gainanov, Damir N.; Golubev, Oleg A.; Kolmogortsev, Ilya D.; Konygin, Anton V.
2016-06-01
The paper is devoted to the problem of scheduling for the linear section of a single-track railway: how to organize the flow in both directions in the most efficient way. In this paper, the authors propose an algorithm for scheduling, examine the properties of this algorithm and perform the computational experiments.
Electric power scheduling - A distributed problem-solving approach
NASA Technical Reports Server (NTRS)
Mellor, Pamela A.; Dolce, James L.; Krupp, Joseph C.
1990-01-01
Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity.
Electric power scheduling: A distributed problem-solving approach
NASA Technical Reports Server (NTRS)
Mellor, Pamela A.; Dolce, James L.; Krupp, Joseph C.
1990-01-01
Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity. The value-driven free-market economic model is such a tool.
Solving a real-world problem using an evolving heuristically driven schedule builder.
Hart, E; Ross, P; Nelson, J
1998-01-01
This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem. PMID:10021741
Solving scheduling tournament problems using a new version of CLONALG
NASA Astrophysics Data System (ADS)
Pérez-Cáceres, Leslie; Riff, María Cristina
2015-01-01
The travelling tournament problem (TTP) is an important and well-known problem within the collective sports research community. The problem is NP-hard which makes difficult finding quality solution in short amount of time. Recently a new kind of TTP has been proposed 'The Relaxed Travelling Tournament Problem'. This version of the problem allows teams to have some days off during the tournament. In this paper, we propose an immune algorithm that is able to solve both problem versions. The algorithm uses moves which are based on the team home/away patterns. One of these moves has been specially designed for the relaxed travel tournament instances. We have tested the algorithm using well-known problem benchmarks and the results obtained are very encouraging.
Solving Stochastic Flexible Flow Shop Scheduling Problems with a Decomposition-Based Approach
NASA Astrophysics Data System (ADS)
Wang, K.; Choi, S. H.
2010-06-01
Real manufacturing is dynamic and tends to suffer a lot of uncertainties. Research on production scheduling under uncertainty has recently received much attention. Although various approaches have been developed for scheduling under uncertainty, this problem is still difficult to tackle by any single approach, because of its inherent difficulties. This chapter describes a decomposition-based approach (DBA) for makespan minimisation of a flexible flow shop (FFS) scheduling problem with stochastic processing times. The DBA decomposes an FFS into several machine clusters which can be solved more easily by different approaches. A neighbouring K-means clustering algorithm is developed to firstly group the machines of an FFS into an appropriate number of machine clusters, based on a weighted cluster validity index. A back propagation network (BPN) is then adopted to assign either the Shortest Processing Time (SPT) Algorithm or the Genetic Algorithm (GA) to generate a sub-schedule for each machine cluster. After machine grouping and approach assignment, an overall schedule is generated by integrating the sub-schedules of the machine clusters. Computation results reveal that the DBA is superior to SPT and GA alone for FFS scheduling under stochastic processing times, and that it can be easily adapted to schedule FFS under other uncertainties.
Three-index Model for Westenberger-Kallrath Benchmark Scheduling Problem
NASA Astrophysics Data System (ADS)
Vooradi, Ramsagar; Shaik, Munawar A.; Gupta, Nikhil M.
2010-10-01
Short-term scheduling of batch operations has become an important research area in the last two decades. Recently Shaik and Floudas (2009) proposed a novel unified model for short-term scheduling using unit-specific event based continuous time representation employing three-index binary and continuous variables. In this work, we extend this three index model to solve a challenging benchmark problem from the scheduling literature that covers most of the features contributing to the complexity of batch process scheduling in industry. In order to implement the problem, new sets of constraints and modifications are incorporated into the three-index model. The different demand instances of the benchmark problem have been solved using the developed model and the results are compared with the literature to demonstrate the effectiveness of the proposed three-index model.
On scheduling models for the frequency interval assignment problem with cumulative interferences
NASA Astrophysics Data System (ADS)
Kiatmanaroj, Kata; Artigues, Christian; Houssin, Laurent
2016-05-01
In this article, models and methods for solving a real-life frequency assignment problem based on scheduling theory are investigated. A realistic frequency assignment problem involving cumulative interference constraints in which the aim is to maximize the number of assigned users is considered. If interferences are assumed to be binary, a multiple carrier frequency assignment problem can be treated as a disjunctive scheduling problem since a user requesting a number of contiguous frequencies can be considered as a non-preemptive task with a processing time, and two interfering users can be modelled through a disjunctive constraint on the corresponding tasks. A binary interference version of the problem is constructed and a disjunctive scheduling model is derived. Based on the binary representation, two models are proposed. The first one relies on an interference matrix and the second one considers maximal cliques. A third, cumulative, model that yields a new class of scheduling problems is also proposed. Computational experiments show that the case-study frequency assignment problem can be solved efficiently with disjunctive scheduling techniques.
An efficient game for vehicle-to-grid coordination problems in smart grids
NASA Astrophysics Data System (ADS)
Shi, Xingyu; Ma, Zhongjing
2015-11-01
Emerging plug-in electric vehicles (PEVs), as distributed energy sources, are promising to provide vehicle-to-grid (V2G) services for power grids, like frequency and voltage regulations, by coordinating their active and reactive power rates. However, due to the autonomy of PEVs, it is challenging how to efficiently schedule the coordination behaviours among these units in a distributed way. In this paper, we formulate the underlying coordination problems as a novel class of Vickrey-Clarke-Groves style (VCG-style) auction games where players, power grids and PEVs do not report a full cost or valuation function but only a multidimensional bid signal: the maximum active and reactive power quantities that a power grid wants and the maximum per unit prices it is willing to pay, and the maximum active and reactive power quantities that a PEV can provide and the minimum per unit prices it asks for. We show the existence of the efficient Nash equilibrium (NE) for the underlying auction games, though there may exist other inefficient NEs. In order to deal with large-scale PEVs, we design games with aggregator players each of which submits bid profiles representing the overall utility for a collection of PEVs, and extend the so-called quantised-progressive second price mechanism to the underlying auction games to implement the efficient NE.
Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems
NASA Technical Reports Server (NTRS)
Heyward, Ann O.
1989-01-01
A two-stage heuristic solution approach for a class of multiobjective, n-job, 1-machine scheduling problems is described. Minimization of job-to-job interference for n jobs is sought. The first stage generates alternative schedule sequences by interchanging pairs of schedule elements. The set of alternative sequences can represent nodes of a decision tree; each node is reached via decision to interchange job elements. The second stage selects the parent node for the next generation of alternative sequences through automated paired comparison of objective performance for all current nodes. An application of the heuristic approach to communications satellite systems planning is presented.
A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements
NASA Astrophysics Data System (ADS)
Pu, Xun; Lu, XianLiang
2011-10-01
Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.
Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems
NASA Astrophysics Data System (ADS)
Cruz-Chávez, Marco Antonio
2015-11-01
This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.
ERIC Educational Resources Information Center
Tsakanikos, Elias; Underwood, Lisa; Sturmey, Peter; Bouras, Nick; McCarthy, Jane
2011-01-01
The present study employed the Disability Assessment Schedule (DAS) to assess problem behaviors in a large sample of adults with ID (N = 568) and evaluate the psychometric properties of this instrument. Although the DAS problem behaviors were found to be internally consistent (Cronbach's [alpha] = 0.87), item analysis revealed one weak item…
NASA Technical Reports Server (NTRS)
Wang, Lui; Valenzuela-Rendon, Manuel
1993-01-01
The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.
Automated telescope scheduling
NASA Technical Reports Server (NTRS)
Johnston, Mark D.
1988-01-01
With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.
Automated telescope scheduling
NASA Astrophysics Data System (ADS)
Johnston, Mark D.
1988-08-01
With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.
ERIC Educational Resources Information Center
Kratochvil, Daniel W.
Variable Modular Scheduling Via Computer, a scheduling program which focuses on allocating a school's resources according to the school's overall purposes, is designed to allow schools to adapt organizational patterns to whatever teaching and learning patterns they define as necessary in meeting their educational goals. The system's rationale,…
ERIC Educational Resources Information Center
Wagner, Matthias Oliver; Bos, Klaus; Jascenoka, Julia; Jekauc, Darko; Petermann, Franz
2012-01-01
The aim of this study was to gain insights into the relationship between developmental coordination disorder, peer problems, and behavioral problems in school-aged children where both internalizing and externalizing behavioral problems were considered. We assumed that the relationship between developmental coordination disorder and…
Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach
NASA Technical Reports Server (NTRS)
Globus, Al; Crawford, James; Lohn, Jason; Morris, Robert; Clancy, Daniel (Technical Monitor)
2002-01-01
We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.
Solution of the NP-hard total tardiness minimization problem in scheduling theory
NASA Astrophysics Data System (ADS)
Lazarev, A. A.
2007-06-01
The classical NP-hard (in the ordinary sense) problem of scheduling jobs in order to minimize the total tardiness for a single machine 1‖Σ T j is considered. An NP-hard instance of the problem is completely analyzed. A procedure for partitioning the initial set of jobs into subsets is proposed. Algorithms are constructed for finding an optimal schedule depending on the number of subsets. The complexity of the algorithms is O( n 2Σ p j ), where n is the number of jobs and p j is the processing time of the jth job ( j = 1, 2, …, n).
A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems
NASA Astrophysics Data System (ADS)
Thammano, Arit; Teekeng, Wannaporn
2015-05-01
The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
NASA Astrophysics Data System (ADS)
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
Some single-machine scheduling problems with learning effects and two competing agents.
Li, Hongjie; Li, Zeyuan; Yin, Yunqiang
2014-01-01
This study considers a scheduling environment in which there are two agents and a set of jobs, each of which belongs to one of the two agents and its actual processing time is defined as a decreasing linear function of its starting time. Each of the two agents competes to process its respective jobs on a single machine and has its own scheduling objective to optimize. The objective is to assign the jobs so that the resulting schedule performs well with respect to the objectives of both agents. The objective functions addressed in this study include the maximum cost, the total weighted completion time, and the discounted total weighted completion time. We investigate three problems arising from different combinations of the objectives of the two agents. The computational complexity of the problems is discussed and solution algorithms where possible are presented. PMID:25009829
Some Single-Machine Scheduling Problems with Learning Effects and Two Competing Agents
Li, Hongjie; Li, Zeyuan; Yin, Yunqiang
2014-01-01
This study considers a scheduling environment in which there are two agents and a set of jobs, each of which belongs to one of the two agents and its actual processing time is defined as a decreasing linear function of its starting time. Each of the two agents competes to process its respective jobs on a single machine and has its own scheduling objective to optimize. The objective is to assign the jobs so that the resulting schedule performs well with respect to the objectives of both agents. The objective functions addressed in this study include the maximum cost, the total weighted completion time, and the discounted total weighted completion time. We investigate three problems arising from different combinations of the objectives of the two agents. The computational complexity of the problems is discussed and solution algorithms where possible are presented. PMID:25009829
NASA Astrophysics Data System (ADS)
Marwati, Rini; Yulianti, Kartika; Pangestu, Herny Wulandari
2016-02-01
A fuzzy evolutionary algorithm is an integration of an evolutionary algorithm and a fuzzy system. In this paper, we present an application of a genetic algorithm to a fuzzy evolutionary algorithm to detect and to solve chromosomes conflict. A chromosome conflict is identified by existence of any two genes in a chromosome that has the same values as two genes in another chromosome. Based on this approach, we construct an algorithm to solve a lecture scheduling problem. Time codes, lecture codes, lecturer codes, and room codes are defined as genes. They are collected to become chromosomes. As a result, the conflicted schedule turns into chromosomes conflict. Built in the Delphi program, results show that the conflicted lecture schedule problem is solvable by this algorithm.
Active Solution Space and Search on Job-shop Scheduling Problem
NASA Astrophysics Data System (ADS)
Watanabe, Masato; Ida, Kenichi; Gen, Mitsuo
In this paper we propose a new searching method of Genetic Algorithm for Job-shop scheduling problem (JSP). The coding method that represent job number in order to decide a priority to arrange a job to Gannt Chart (called the ordinal representation with a priority) in JSP, an active schedule is created by using left shift. We define an active solution at first. It is solution which can create an active schedule without using left shift, and set of its defined an active solution space. Next, we propose an algorithm named Genetic Algorithm with active solution space search (GA-asol) which can create an active solution while solution is evaluated, in order to search the active solution space effectively. We applied it for some benchmark problems to compare with other method. The experimental results show good performance.
ERIC Educational Resources Information Center
Borrero, Carrie S. W.; Vollmer, Timothy R.; Borrero, John C.; Bourret, Jason C.; Sloman, Kimberly N.; Samaha, Andrew L.; Dallery, Jesse
2010-01-01
This study evaluated how children who exhibited functionally equivalent problem and appropriate behavior allocate responding to experimentally arranged reinforcer rates. Relative reinforcer rates were arranged on concurrent variable-interval schedules and effects on relative response rates were interpreted using the generalized matching equation.…
An information theoretic view of the scheduling problem in whole-body CAD
NASA Astrophysics Data System (ADS)
Zhan, Yiqiang; Zhou, Xiang Sean; Krishnan, Arun
2008-03-01
Emerging whole-body imaging technologies push computer aided detection/diagnosis (CAD) to scale up to a whole-body level, which involves multiple organs or anatomical structure. To be exploited in this paper is the fact that the various tasks in whole-body CAD are often highly dependent (e.g., the localization of the femur heads strongly predicts the position of the iliac bifurcation of the aorta). One way to effectively employ task dependency is to schedule the tasks such that outputs of some tasks are used to guide the others. In this sense, optimal task scheduling is key to improve overall performance of a whole-body CAD system. In this paper, we propose a method for task scheduling that is optimal in an information-theoretic sense. The central idea is to schedule tasks in such an order that each operation achieves maximum expected information gain over all the tasks. The formulation embeds two intuitive principles: (1) a task with higher confidence tends to be scheduled earlier; (2) a task with higher predictive power for other tasks tends to be scheduled earlier. More specifically, task dependency is modeled by conditional probability; the outcome of each task is assumed to be probabilistic as well; and the objective function is based on the reduction of the summed conditional entropy over all tasks. The validation is carried out on a challenging CAD problem, multi-organ localization in whole-body CT. Compared to unscheduled and ad hoc scheduled organ detection/localization, our scheduled execution achieves higher accuracy with much less computation time.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem
Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue
2015-01-01
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods. PMID:26176764
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.
Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue
2015-01-01
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods. PMID:26176764
NASA Astrophysics Data System (ADS)
Konno, Yohko; Suzuki, Keiji
This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.
Morrow, Daniel; Raquel, Liza; Schriver, Angela; Redenbo, Seth; Rozovski, David; Weiss, Gillian
2008-09-01
Taking medication requires developing plans to accomplish the activity. This planning challenges older adults because of age-related cognitive limits and inadequate collaboration with health providers. The authors investigated whether an external aid (medtable) supports collaborative planning in the context of a simulated patient/provider task in which pairs of older adults worked together to create medication schedules. Experiment 1 compared pairs who used the medtable, blank paper (unstructured aid), or no aid to create schedules varying in complexity of medication constraints (number of medications and medication co-occurrence restrictions) and patient constraints (available times during the day to take medication). Both aids increased problem-solving accuracy and efficiency (time per unit accuracy) compared to the no-aid condition, primarily for more complex schedules. However, benefits were similar for the two aids. In Experiment 2, a redesigned medtable increased problem-solving accuracy and efficiency compared to blank paper. Both aids presumably supported problem solving by providing a jointly visible workspace for developing schedules. The medtable may be more effective because it externalizes constraints (relationships between medication and patient information), so that participants can more easily organize information. PMID:18808282
Compound Words: A Problem in Post-Coordinate Retrieval Systems
ERIC Educational Resources Information Center
Jones, Kevin P.
1971-01-01
Compound words cause some difficulty in post-coordinate indexing systems: if too many are fractured, or the wrong categories are selected for fracturing noise will be produced at unacceptable levels on retrieval. (Author/MM)
NASA Astrophysics Data System (ADS)
Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju
2014-04-01
Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.
Minimizing conflicts: A heuristic repair method for constraint-satisfaction and scheduling problems
NASA Technical Reports Server (NTRS)
Minton, Steve; Johnston, Mark; Philips, Andrew; Laird, Phil
1992-01-01
This paper describes a simple heuristic approach to solving large-scale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value-ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. The heuristic can be used with a variety of different search strategies. We demonstrate empirically that on the n-queens problem, a technique based on this approach performs orders of magnitude better than traditional backtracking techniques. We also describe a scheduling application where the approach has been used successfully. A theoretical analysis is presented both to explain why this method works well on certain types of problems and to predict when it is likely to be most effective.
Single-machine group scheduling problems with deteriorating and learning effect
NASA Astrophysics Data System (ADS)
Xingong, Zhang; Yong, Wang; Shikun, Bai
2016-07-01
The concepts of deteriorating jobs and learning effects have been individually studied in many scheduling problems. However, most studies considering the deteriorating and learning effects ignore the fact that production efficiency can be increased by grouping various parts and products with similar designs and/or production processes. This phenomenon is known as 'group technology' in the literature. In this paper, a new group scheduling model with deteriorating and learning effects is proposed, where learning effect depends not only on job position, but also on the position of the corresponding job group; deteriorating effect depends on its starting time of the job. This paper shows that the makespan and the total completion time problems remain polynomial optimal solvable under the proposed model. In addition, a polynomial optimal solution is also presented to minimise the maximum lateness problem under certain agreeable restriction.
Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly
2014-01-01
We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures. PMID:25610911
Manipulating Tabu List to Handle Machine Breakdowns in Job Shop Scheduling Problems
NASA Astrophysics Data System (ADS)
Nababan, Erna Budhiarti; SalimSitompul, Opim
2011-06-01
Machine breakdowns in a production schedule may occur on a random basis that make the well-known hard combinatorial problem of Job Shop Scheduling Problems (JSSP) becomes more complex. One of popular techniques used to solve the combinatorial problems is Tabu Search. In this technique, moves that will be not allowed to be revisited are retained in a tabu list in order to avoid in gaining solutions that have been obtained previously. In this paper, we propose an algorithm to employ a second tabu list to keep broken machines, in addition to the tabu list that keeps the moves. The period of how long the broken machines will be kept on the list is categorized using fuzzy membership function. Our technique are tested to the benchmark data of JSSP available on the OR library. From the experiment, we found that our algorithm is promising to help a decision maker to face the event of machine breakdowns.
Genetic Algorithm to minimize flowtime in a no-wait flowshop scheduling problem
NASA Astrophysics Data System (ADS)
Chaudhry, Imran A.; Ahmed, Riaz; Munem Khan, Abdul
2014-07-01
No-wait flowshop is an important scheduling environment having application in many industries. This paper addresses a no-wait flowshop scheduling problem, where the objective function is to minimise total flowtime. A Genetic Algorithm (GA) optimization approach implemented in a spreadsheet environment is suggested to solve this important class of problem. The proposed algorithm employs a general purpose genetic algorithm which can be customised with ease to address any objective function without modifying the optimization routine. Performance of the proposed approach is compared with eight previously reported algorithms for two sets of benchmark problems. Experimental analysis shows that the performance of the suggested approach is comparable with earlier approaches in terms of quality of solution.
A Solution Method of Scheduling Problem with Worker Allocation by a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Osawa, Akira; Ida, Kenichi
In a scheduling problem with worker allocation (SPWA) proposed by Iima et al, the worker's skill level to each machine is all the same. However, each worker has a different skill level for each machine in the real world. For that reason, we propose a new model of SPWA in which a worker has the different skill level to each machine. To solve the problem, we propose a new GA for SPWA consisting of the following new three procedures, shortening of idle time, modifying infeasible solution to feasible solution, and a new selection method for GA. The effectiveness of the proposed algorithm is clarified by numerical experiments using benchmark problems for job-shop scheduling.
48 CFR 552.236-78 - Shop Drawings, Coordination Drawings, and Schedules.
Code of Federal Regulations, 2010 CFR
2010-10-01
... coordination drawing shall have a blank area 5 by 5 inches, located adjacent to the title block. The title block shall display the following: Number and title of drawing Date of drawing or revision Name...
ERIC Educational Resources Information Center
Waters, Melissa B.; Lerman, Dorothea C.; Hovanetz, Alyson N.
2009-01-01
The separate and combined effects of visual schedules and extinction plus differential reinforcement of other behavior (DRO) were evaluated to decrease transition-related problem behavior of 2 children diagnosed with autism. Visual schedules alone were ineffective in reducing problem behavior when transitioning from preferred to nonpreferred…
NASA Astrophysics Data System (ADS)
Ramli, Razamin; Tein, Lim Huai
2016-08-01
A good work schedule can improve hospital operations by providing better coverage with appropriate staffing levels in managing nurse personnel. Hence, constructing the best nurse work schedule is the appropriate effort. In doing so, an improved selection operator in the Evolutionary Algorithm (EA) strategy for a nurse scheduling problem (NSP) is proposed. The smart and efficient scheduling procedures were considered. Computation of the performance of each potential solution or schedule was done through fitness evaluation. The best so far solution was obtained via special Maximax&Maximin (MM) parent selection operator embedded in the EA, which fulfilled all constraints considered in the NSP.
Enhancements of evolutionary algorithm for the complex requirements of a nurse scheduling problem
NASA Astrophysics Data System (ADS)
Tein, Lim Huai; Ramli, Razamin
2014-12-01
Over the years, nurse scheduling is a noticeable problem that is affected by the global nurse turnover crisis. The more nurses are unsatisfied with their working environment the more severe the condition or implication they tend to leave. Therefore, the current undesirable work schedule is partly due to that working condition. Basically, there is a lack of complimentary requirement between the head nurse's liability and the nurses' need. In particular, subject to highly nurse preferences issue, the sophisticated challenge of doing nurse scheduling is failure to stimulate tolerance behavior between both parties during shifts assignment in real working scenarios. Inevitably, the flexibility in shifts assignment is hard to achieve for the sake of satisfying nurse diverse requests with upholding imperative nurse ward coverage. Hence, Evolutionary Algorithm (EA) is proposed to cater for this complexity in a nurse scheduling problem (NSP). The restriction of EA is discussed and thus, enhancement on the EA operators is suggested so that the EA would have the characteristic of a flexible search. This paper consists of three types of constraints which are the hard, semi-hard and soft constraints that can be handled by the EA with enhanced parent selection and specialized mutation operators. These operators and EA as a whole contribute to the efficiency of constraint handling, fitness computation as well as flexibility in the search, which correspond to the employment of exploration and exploitation principles.
Meta-RaPS Algorithm for the Aerial Refueling Scheduling Problem
NASA Technical Reports Server (NTRS)
Kaplan, Sezgin; Arin, Arif; Rabadi, Ghaith
2011-01-01
The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on multiple tankers (machines). ARSP assumes that jobs have different release times and due dates, The total weighted tardiness is used to evaluate schedule's quality. Therefore, ARSP can be modeled as a parallel machine scheduling with release limes and due dates to minimize the total weighted tardiness. Since ARSP is NP-hard, it will be more appropriate to develop a pproimate or heuristic algorithm to obtain solutions in reasonable computation limes. In this paper, Meta-Raps-ATC algorithm is implemented to create high quality solutions. Meta-RaPS (Meta-heuristic for Randomized Priority Search) is a recent and promising meta heuristic that is applied by introducing randomness to a construction heuristic. The Apparent Tardiness Rule (ATC), which is a good rule for scheduling problems with tardiness objective, is used to construct initial solutions which are improved by an exchanging operation. Results are presented for generated instances.
NASA Astrophysics Data System (ADS)
Wang, Deyun; Grunder, Olivier; EL Moudni, Abdellah
2014-08-01
This paper considers an integrated lot sizing and scheduling problem for a production-distribution environment with arbitrary job volumes and distinct due dates considerations. In the problem, jobs are firstly batch processed on a batching machine at production stage and then delivered to a pre-specified customer at the subsequent delivery stage by a capacitated vehicle. Each job is associated with a distinct due date and a distinct volume, and has to be delivered to the customer before its due date, i.e. delay is not allowed. The processing time of a batch is a constant independent of the jobs it contains. In production, a constant set-up time as well as a constant set-up cost is required before the first job of this batch is processed. In delivery, a constant delivery time as well as a constant delivery cost is needed for each round-trip delivery between the factory and the customer. Moreover, it is supposed that a job that arrives at the customer before its due date will incur a customer inventory cost. The objective is to find a coordinated lot sizing and scheduling scheme such that the total cost is minimised while guaranteeing a certain customer service level. A mixed integer formulation is proposed for this problem, and then a genetic algorithm is developed to solve it. To evaluate the performance of the proposed genetic algorithm, a lower bound on the objective value is established. Computational experiments show that the proposed genetic algorithm performs well on randomly generated problem instances.
de Chaves, Raquel Nichele; Bustamante Valdívia, Alcibíades; Nevill, Alan; Freitas, Duarte; Tani, Go; Katzmarzyk, Peter T; Maia, José António Ribeiro
2016-01-01
The aims of this cross-sectional study were to examine the developmental characteristics (biological maturation and body size) associated with gross motor coordination problems in 5193 Peruvian children (2787 girls) aged 6-14 years from different geographical locations, and to investigate how the probability that children suffer with gross motor coordination problems varies with physical fitness. Children with gross motor coordination problems were more likely to have lower flexibility and explosive strength levels, having adjusted for age, sex, maturation and study site. Older children were more likely to suffer from gross motor coordination problems, as were those with greater body mass index. However, more mature children were less likely to have gross motor coordination problems, although children who live at sea level or at high altitude were more likely to suffer from gross motor coordination problems than children living in the jungle. Our results provide evidence that children and adolescents with lower physical fitness are more likely to have gross motor coordination difficulties. The identification of youths with gross motor coordination problems and providing them with effective intervention programs is an important priority in order to overcome such developmental problems, and help to improve their general health status. PMID:26871464
Duan, Qian-Qian; Yang, Gen-Ke; Pan, Chang-Chun
2014-01-01
A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The heuristic returned by the FSM can guide the GA algorithm towards good solutions. The idea behind this is that we can generate promising substructure or partial solution by using FSM. Furthermore, the FSM can guarantee that the entire solution space is uniformly covered. Therefore, the combination of the two algorithms has better global performance than the existing GA or FSM which is operated individually. Finally, a real-life crude oil scheduling problem from the literature is used for conducting simulation. The experimental results validate that the proposed method outperforms the state-of-art GA method. PMID:24772031
A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs
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
Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem
Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh
2014-01-01
This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359
Hybrid metaheuristics for solving a fuzzy single batch-processing machine scheduling problem.
Molla-Alizadeh-Zavardehi, S; Tavakkoli-Moghaddam, R; Lotfi, F Hosseinzadeh
2014-01-01
This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359
NASA Astrophysics Data System (ADS)
Bai, Danyu; Zhang, Zhihai
2014-08-01
This article investigates the open-shop scheduling problem with the optimal criterion of minimising the sum of quadratic completion times. For this NP-hard problem, the asymptotic optimality of the shortest processing time block (SPTB) heuristic is proven in the sense of limit. Moreover, three different improvements, namely, the job-insert scheme, tabu search and genetic algorithm, are introduced to enhance the quality of the original solution generated by the SPTB heuristic. At the end of the article, a series of numerical experiments demonstrate the convergence of the heuristic, the performance of the improvements and the effectiveness of the quadratic objective.
NASA Astrophysics Data System (ADS)
Zhu, Li; He, Yongxiang; Xue, Haidong; Chen, Leichen
Traditional genetic algorithms (GA) displays a disadvantage of early-constringency in dealing with scheduling problem. To improve the crossover operators and mutation operators self-adaptively, this paper proposes a self-adaptive GA at the target of multitask scheduling optimization under limited resources. The experiment results show that the proposed algorithm outperforms the traditional GA in evolutive ability to deal with complex task scheduling optimization.
NASA Astrophysics Data System (ADS)
Jafari, Hamed; Salmasi, Nasser
2015-04-01
The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.
Laplace Boundary-Value Problem in Paraboloidal Coordinates
ERIC Educational Resources Information Center
Duggen, L.; Willatzen, M.; Voon, L. C. Lew Yan
2012-01-01
This paper illustrates both a problem in mathematical physics, whereby the method of separation of variables, while applicable, leads to three ordinary differential equations that remain fully coupled via two separation constants and a five-term recurrence relation for series solutions, and an exactly solvable problem in electrostatics, as a…
Preserving spherical symmetry in axisymmetric coordinates for diffusion problems
Brunner, T. A.; Kolev, T. V.; Bailey, T. S.; Till, A. T.
2013-07-01
Persevering symmetric solutions, even in the under-converged limit, is important to the robustness of production simulation codes. We explore the symmetry preservation in both a continuous nodal and a mixed finite element method. In their standard formulation, neither method preserves spherical solution symmetry in axisymmetric (RZ) coordinates. We propose two methods, one for each family of finite elements, that recover spherical symmetry for low-order finite elements on linear or curvilinear meshes. This is a first step toward understanding achieving symmetry for higher-order elements. (authors)
Coordinated Observations of Space Debris as Optimisation Problem of Inter-Dependent Metrics
NASA Astrophysics Data System (ADS)
Sciotti, M.; Charlish, A.
2013-08-01
Optimal allocation of sensor resources is addressed in this paper in the frame of space surveillance application. Inspiration is taken from the optimal management of multi-functional sensors and netted surveillance sensors, for which the Sensor Management problem is often addressed as a Markov Decision Process. This approach allows determining the optimal decision at each discrete time instant by quantifying the expected payoff coming from the selected action. An action might be the assignment of the i -th surveillance task to the m -th sensor in the network ('tasking'), the selection of the i -th task at the k -th time slot ('scheduling'), or the activation of a specific sensor configuration for the completion of the i -th task ('resource allocation'). The common objective is the maximization of the global reward coming from the selected sequence of actions over a finite or infinite time horizon. This leads to a sequence of coordinated observations carried out by the sensor(s), which are determined statically or dynamically by the Sensor Manager. In this paper, the allocation of space surveillance resources is analysed as a management problem for sensor(s) with finite resources. The proposed allocation is driven by the operational requirements for space objects cataloguing, such as the object population coverage and the track accuracy. A sequential resource allocation strategy is formulated in order to cope with such inter-dependent, concurring performance metrics. The approach can be also extended to multiple sensors with different performance or nature. Promising results are demonstrated over a phased array radar case study.
NASA Astrophysics Data System (ADS)
Guo, Peng; Cheng, Wenming; Wang, Yi
2014-10-01
The quay crane scheduling problem (QCSP) determines the handling sequence of tasks at ship bays by a set of cranes assigned to a container vessel such that the vessel's service time is minimized. A number of heuristics or meta-heuristics have been proposed to obtain the near-optimal solutions to overcome the NP-hardness of the problem. In this article, the idea of generalized extremal optimization (GEO) is adapted to solve the QCSP with respect to various interference constraints. The resulting GEO is termed the modified GEO. A randomized searching method for neighbouring task-to-QC assignments to an incumbent task-to-QC assignment is developed in executing the modified GEO. In addition, a unidirectional search decoding scheme is employed to transform a task-to-QC assignment to an active quay crane schedule. The effectiveness of the developed GEO is tested on a suite of benchmark problems introduced by K.H. Kim and Y.M. Park in 2004 (European Journal of Operational Research, Vol. 156, No. 3). Compared with other well-known existing approaches, the experiment results show that the proposed modified GEO is capable of obtaining the optimal or near-optimal solution in a reasonable time, especially for large-sized problems.
A Hybrid Cellular Genetic Algorithm for Multi-objective Crew Scheduling Problem
NASA Astrophysics Data System (ADS)
Jolai, Fariborz; Assadipour, Ghazal
Crew scheduling is one of the important problems of the airline industry. This problem aims to cover a number of flights by crew members, such that all the flights are covered. In a robust scheduling the assignment should be so that the total cost, delays, and unbalanced utilization are minimized. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimization method. The proposed algorithm provides the decision maker with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Evaluating the performance of the proposed algorithm, three metrics are suggested, and the diversity and the convergence of the achieved Pareto front are appraised. Finally a comparison is made between CellDE and PAES, another meta-heuristic algorithm. The results show the superiority of CellDE.
A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem
NASA Astrophysics Data System (ADS)
Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao
A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.
Solving a Production Scheduling Problem by Means of Two Biobjective Metaheuristic Procedures
NASA Astrophysics Data System (ADS)
Toncovich, Adrián; Oliveros Colay, María José; Moreno, José María; Corral, Jiménez; Corral, Rafael
2009-11-01
Production planning and scheduling problems emphasize the need for the availability of management tools that can help to assure proper service levels to customers, maintaining, at the same time, the production costs at acceptable levels and maximizing the utilization of the production facilities. In this case, a production scheduling problem that arises in the context of the activities of a company dedicated to the manufacturing of furniture for children and teenagers is addressed. Two bicriteria metaheuristic procedures are proposed to solve the sequencing problem in a production equipment that constitutes the bottleneck of the production process of the company. The production scheduling problem can be characterized as a general flow shop with sequence dependant setup times and additional inventory constraints. Two objectives are simultaneously taken into account when the quality of the candidate solutions is evaluated: the minimization of completion time of all jobs, or makespan, and the minimization of the total flow time of all jobs. Both procedures are based on a local search strategy that responds to the structure of the simulated annealing metaheuristic. In this case, both metaheuristic approaches generate a set of solutions that provides an approximation to the optimal Pareto front. In order to evaluate the performance of the proposed techniques a series of experiments was conducted. After analyzing the results, it can be said that the solutions provided by both approaches are adequate from the viewpoint of the quality as well as the computational effort involved in their generation. Nevertheless, a further refinement of the proposed procedures should be implemented with the aim of facilitating a quasi-automatic definition of the solution parameters.
ERIC Educational Resources Information Center
Earnest, Darrell
2015-01-01
This article reports on students' problem-solving approaches across three representations--number lines, coordinate planes, and function graphs--the axes of which conventional mathematics treats in terms of consistent geometric and numeric coordinations. I consider these representations to be a part of a "hierarchical representational…
A network flow model for short-term hydro-dominated hydrothermal scheduling problems
Franco, P.E.C. ); Carvalho, M.F. ); Soares, S. )
1994-05-01
This paper is concerned with the Short-Term Hydrothermal Scheduling (STHS) of hydro-dominated power systems. The problem's formulation includes the representation of operational constraints such as the hydraulic coupling between hydro plants in cascade and the transmission limits in the electric network. In order to allow the problem's decomposition into hydraulic and electric subproblems, a linear-quadratic penalty approach is applied to enforce the coupling between hydro and electric variables. As a result, the problem's natural network flow structure is fully exploited through special-purposed network flow algorithms. The technique has been implemented in FORTRAN in a SUN SPARCstation IPX and tested in a 440 KV subsystem of the main interconnected Brazilian power system.
Three-Stage Tabu Search for Solving Large-Scale Flow Shop Scheduling Problems
NASA Astrophysics Data System (ADS)
Xu, Yuedong; Tian, Yajie; Sannomiya, Nobuo
Tabu search is a meta-heuristic approach designed skillfully for finding a suboptimal solution of combinatorial optimization problems. In this paper the tabu search with three stages is proposed for solving large-scale flow shop scheduling problems. In order to obtain a better suboptimal solution in a short computation time, three different candidate lists are used to determine the incumbent solution in the respective search stages. The candidate lists are constructed by restricting the moving of each job. Test problems with four kinds of job data are examined. Based on analyzing the relationship between the candidate list and the suboptimal solution for each job data, a common parameter is given to construct the candidate list during the search process. Comparison of the computation result is made with the genetic algorithm and the basic tabu search, from which it is shown that the proposed tabu search outperforms two others.
NASA Astrophysics Data System (ADS)
Ohno, Akiyoshi; Nishi, Tatsushi; Inuiguchi, Masahiro; Takahashi, Satoru; Ueda, Kenji
In this paper, we propose a column generation for the train-set scheduling problem with regular maintenance constraints. The problem is to allocate the minimum train-set to the train operations required to operate a given train timetable. In the proposed method, a tight lower bound can be obtained from the continuous relaxation for Dantzig-Wolfe reformulation by column generation. The subproblem for the column generation is an elementary shortest path problem with resource constraints. A labeling algorithm is applied to solve the subproblem. In order to reduce the computational effort for solving subproblems, a new state space relaxation of the subproblem is developed in the labeling algorithm. An upper bound is computed by a heuristic algorithm. Computational results demonstrate the effectiveness of the proposed method.
An estimation of distribution algorithm (EDA) variant with QGA for Flowshop scheduling problem
NASA Astrophysics Data System (ADS)
Latif, Muhammad Shahid; Hong, Zhou; Ali, Amir
2014-04-01
In this research article, a hybrid approach is presented which based on well-known meta-heuristics algorithms. This study based on integration of Quantum Genetic Algorithm (QGA) and Estimation of Distribution Algorithm, EDA, (for simplicity we use Q-EDA) for flowshop scheduling, a well-known NP hard Problem, while focusing on the total flow time minimization criterion. A relatively new method has been adopted for the encoding of jobs sequence in flowshop known as angel rotations instead of random keys, so QGA become more efficient. Further, EDA has been integrated to update the population of QGA by making a probability model. This probabilistic model is built and used to generate new candidate solutions which comprised on best individuals, obtained after several repetitions of proposed (Q-EDA) approach. As both heuristics based on probabilistic characteristics, so exhibits excellent learning capability and have minimum chances of being trapped in local optima. The results obtained during this study are presented and compared with contemporary approaches in literature. The current hybrid Q-EDA has implemented on different benchmark problems. The experiments has showed better convergence and results. It is concluded that hybrid Q-EDA algorithm can generally produce better results while implemented for Flowshop Scheduling Problem (FSSP).
Internal or shape coordinates in the {ital n}-body problem
Littlejohn, R.G.; Reinsch, M.
1995-09-01
The construction of global shape coordinates for the {ital n}-body problem is considered. Special attention is given to the three- and four-body problems. Quantities, including candidates for coordinates, are organized according to their transformation properties under so-called democracy transformations (orthogonal transformations of Jacobi vectors). Important submanifolds of shape space are identified and their topology studied, including the manifolds upon which shapes are coplanar or collinear, and the manifolds upon which the moment of inertia tensor is degenerate.
NASA Astrophysics Data System (ADS)
Li, Kai; Yang, Shan-Lin; Ren, Ming-Lun
2011-10-01
This article considers the single-machine scheduling problem to minimise the total resource consumption under the constraint that the makespan does not exceed a given limit, in which the release date of a job is a linear decreasing continuous function of the resource consumption. This problem is NP-hard in the strong sense. We design a simulated annealing (SA) algorithm to obtain the near-optimal solution with high quality. Two operators, right-move and left-move, are defined and their influences on the resource consumption are analysed. We use two operations, insert and swap, to generate the neighbourhood, and discuss how to calculate the change of total resource consumption. To evaluate the performance of the proposed algorithm, we relax the problem to an assignment problem, and obtain a lower bound by the Hungary method. And then, we improve its quality by Chu's method. Based on the settings that Janiak provided, we generate the random test data in our experiments to simulate the ingot preheating and hot-rolling process in steel mills. The accuracy and efficiency of the proposed SA algorithm are tested based on those data with problem sizes varying from 50 to 200 jobs. The computational results indicate that the SA approach is promising and capable of solving large-scale problems in a reasonable time.
Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie
2015-01-01
To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA. PMID:26702371
NASA Astrophysics Data System (ADS)
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2014-09-01
In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.
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.
NASA Astrophysics Data System (ADS)
Gao, Qian
For both the conventional radio frequency and the comparably recent optical wireless communication systems, extensive effort from the academia had been made in improving the network spectrum efficiency and/or reducing the error rate. To achieve these goals, many fundamental challenges such as power efficient constellation design, nonlinear distortion mitigation, channel training design, network scheduling and etc. need to be properly addressed. In this dissertation, novel schemes are proposed accordingly to deal with specific problems falling in category of these challenges. Rigorous proofs and analyses are provided for each of our work to make a fair comparison with the corresponding peer works to clearly demonstrate the advantages. The first part of this dissertation considers a multi-carrier optical wireless system employing intensity modulation (IM) and direct detection (DD). A block-wise constellation design is presented, which treats the DC-bias that conventionally used solely for biasing purpose as an information basis. Our scheme, we term it MSM-JDCM, takes advantage of the compactness of sphere packing in a higher dimensional space, and in turn power efficient constellations are obtained by solving an advanced convex optimization problem. Besides the significant power gains, the MSM-JDCM has many other merits such as being capable of mitigating nonlinear distortion by including a peak-to-power ratio (PAPR) constraint, minimizing inter-symbol-interference (ISI) caused by frequency-selective fading with a novel precoder designed and embedded, and further reducing the bit-error-rate (BER) by combining with an optimized labeling scheme. The second part addresses several optimization problems in a multi-color visible light communication system, including power efficient constellation design, joint pre-equalizer and constellation design, and modeling of different structured channels with cross-talks. Our novel constellation design scheme, termed CSK-Advanced, is
NASA Astrophysics Data System (ADS)
Izah Anuar, Nurul; Saptari, Adi
2016-02-01
This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.
Scheduling of flow shop problems on 3 machines in fuzzy environment with double transport facility
NASA Astrophysics Data System (ADS)
Sathish, Shakeela; Ganesan, K.
2016-06-01
Flow shop scheduling is a decision making problem in production and manufacturing field which has a significant impact on the performance of an organization. When the machines on which jobs are to be processed are placed at different places, the transportation time plays a significant role in production. Further two different transport agents where 1st takes the job from 1st machine to 2nd machine and then returns back to the first machine and the 2nd takes the job from 2nd machine to 3rd machine and then returns back to the 2nd machine are also considered. We propose a method to minimize the total make span; without converting the fuzzy processing time to classical numbers by using a new type of fuzzy arithmetic and a fuzzy ranking method. A numerical example is provided to explain the proposed method.
Three hybridization models based on local search scheme for job shop scheduling problem
NASA Astrophysics Data System (ADS)
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
An extended abstract: A heuristic repair method for constraint-satisfaction and scheduling problems
NASA Technical Reports Server (NTRS)
Minton, Steven; Johnston, Mark D.; Philips, Andrew B.; Laird, Philip
1992-01-01
The work described in this paper was inspired by a surprisingly effective neural network developed for scheduling astronomical observations on the Hubble Space Telescope. Our heuristic constraint satisfaction problem (CSP) method was distilled from an analysis of the network. In the process of carrying out the analysis, we discovered that the effectiveness of the network has little to do with its connectionist implementation. Furthermore, the ideas employed in the network can be implemented very efficiently within a symbolic CSP framework. The symbolic implementation is extremely simple. It also has the advantage that several different search strategies can be employed, although we have found that hill-climbing methods are particularly well-suited for the applications that we have investigated. We begin the paper with a brief review of the neural network. Following this, we describe our symbolic method for heuristic repair.
Decision theory for computing variable and value ordering decisions for scheduling problems
NASA Technical Reports Server (NTRS)
Linden, Theodore A.
1993-01-01
Heuristics that guide search are critical when solving large planning and scheduling problems, but most variable and value ordering heuristics are sensitive to only one feature of the search state. One wants to combine evidence from all features of the search state into a subjective probability that a value choice is best, but there has been no solid semantics for merging evidence when it is conceived in these terms. Instead, variable and value ordering decisions should be viewed as problems in decision theory. This led to two key insights: (1) The fundamental concept that allows heuristic evidence to be merged is the net incremental utility that will be achieved by assigning a value to a variable. Probability distributions about net incremental utility can merge evidence from the utility function, binary constraints, resource constraints, and other problem features. The subjective probability that a value is the best choice is then derived from probability distributions about net incremental utility. (2) The methods used for rumor control in Bayesian Networks are the primary way to prevent cycling in the computation of probable net incremental utility. These insights lead to semantically justifiable ways to compute heuristic variable and value ordering decisions that merge evidence from all available features of the search state.
NASA Astrophysics Data System (ADS)
Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu
2015-12-01
For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.
Li, Shanlin; Li, Maoqin
2015-01-01
We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time. PMID:25785285
Li, Shanlin; Li, Maoqin
2015-01-01
We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time. PMID:25785285
Duan, Qianqian; Yang, Genke; Xu, Guanglin; Pan, Changchun
2014-01-01
This paper is devoted to develop an approximation method for scheduling refinery crude oil operations by taking into consideration the demand uncertainty. In the stochastic model the demand uncertainty is modeled as random variables which follow a joint multivariate distribution with a specific correlation structure. Compared to deterministic models in existing works, the stochastic model can be more practical for optimizing crude oil operations. Using joint chance constraints, the demand uncertainty is treated by specifying proximity level on the satisfaction of product demands. However, the joint chance constraints usually hold strong nonlinearity and consequently, it is still hard to handle it directly. In this paper, an approximation method combines a relax-and-tight technique to approximately transform the joint chance constraints to a serial of parameterized linear constraints so that the complicated problem can be attacked iteratively. The basic idea behind this approach is to approximate, as much as possible, nonlinear constraints by a lot of easily handled linear constraints which will lead to a well balance between the problem complexity and tractability. Case studies are conducted to demonstrate the proposed methods. Results show that the operation cost can be reduced effectively compared with the case without considering the demand correlation. PMID:24757433
High Order Finite Difference Methods, Multidimensional Linear Problems and Curvilinear Coordinates
NASA Technical Reports Server (NTRS)
Nordstrom, Jan; Carpenter, Mark H.
1999-01-01
Boundary and interface conditions are derived for high order finite difference methods applied to multidimensional linear problems in curvilinear coordinates. The boundary and interface conditions lead to conservative schemes and strict and strong stability provided that certain metric conditions are met.
NASA Astrophysics Data System (ADS)
Tang, Dunbing; Dai, Min
2015-09-01
The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.
NASA Astrophysics Data System (ADS)
He, Yong; Sun, Li
2015-05-01
In this paper, we introduce a group scheduling model with general deteriorating jobs and learning effects in which deteriorating jobs and learning effects are both considered simultaneously. This means that the actual processing time of a job depends not only on the processing time of the jobs already processed, but also on its scheduled position. In our model, the group setup times are general linear functions of their starting times and the jobs in the same group have general position-dependent learning effects and time-dependent deterioration. The objective of scheduling problems is to minimise the makespan and the sum of completion times, respectively. We show that the problems remain solvable in polynomial time under the proposed model.
A Solution Method of Job-shop Scheduling Problems by the Idle Time Shortening Type Genetic Algorithm
NASA Astrophysics Data System (ADS)
Ida, Kenichi; Osawa, Akira
In this paper, we propose a new idle time shortening method for Job-shop scheduling problems (JSPs). We insert its method into a genetic algorithm (GA). The purpose of JSP is to find a schedule with the minimum makespan. We suppose that it is effective to reduce idle time of a machine in order to improve the makespan. The left shift is a famous algorithm in existing algorithms for shortening idle time. The left shift can not arrange the work to idle time. For that reason, some idle times are not shortened by the left shift. We propose two kinds of algorithms which shorten such idle time. Next, we combine these algorithms and the reversal of a schedule. We apply GA with its algorithm to benchmark problems and we show its effectiveness.
Finite element method formulation in polar coordinates for transient heat conduction problems
NASA Astrophysics Data System (ADS)
Duda, Piotr
2016-04-01
The aim of this paper is the formulation of the finite element method in polar coordinates to solve transient heat conduction problems. It is hard to find in the literature a formulation of the finite element method (FEM) in polar or cylindrical coordinates for the solution of heat transfer problems. This document shows how to apply the most often used boundary conditions. The global equation system is solved by the Crank-Nicolson method. The proposed algorithm is verified in three numerical tests. In the first example, the obtained transient temperature distribution is compared with the temperature obtained from the presented analytical solution. In the second numerical example, the variable boundary condition is assumed. In the last numerical example the component with the shape different than cylindrical is used. All examples show that the introduction of the polar coordinate system gives better results than in the Cartesian coordinate system. The finite element method formulation in polar coordinates is valuable since it provides a higher accuracy of the calculations without compacting the mesh in cylindrical or similar to tubular components. The proposed method can be applied for circular elements such as boiler drums, outlet headers, flux tubes. This algorithm can be useful during the solution of inverse problems, which do not allow for high density grid. This method can calculate the temperature distribution in the bodies of different properties in the circumferential and the radial direction. The presented algorithm can be developed for other coordinate systems. The examples demonstrate a good accuracy and stability of the proposed method.
NASA Astrophysics Data System (ADS)
Trunfio, Roberto
2015-06-01
In a recent article, Guo, Cheng and Wang proposed a randomized search algorithm, called modified generalized extremal optimization (MGEO), to solve the quay crane scheduling problem for container groups under the assumption that schedules are unidirectional. The authors claim that the proposed algorithm is capable of finding new best solutions with respect to a well-known set of benchmark instances taken from the literature. However, as shown in this note, there are some errors in their work that can be detected by analysing the Gantt charts of two solutions provided by MGEO. In addition, some comments on the method used to evaluate the schedule corresponding to a task-to-quay crane assignment and on the search scheme of the proposed algorithm are provided. Finally, to assess the effectiveness of the proposed algorithm, the computational experiments are repeated and additional computational experiments are provided.
NASA Astrophysics Data System (ADS)
Joo, Cheol Min; Kim, Byung Soo
2012-09-01
This article considers a parallel machine scheduling problem with ready times, due times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines to minimize the weighted sum of setup times, delay times and tardy times. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristics, genetic algorithm (GA) and a new population-based evolutionary meta-heuristic called self-evolution algorithm (SEA), are proposed. The performances of the meta-heuristic algorithms are evaluated through comparison with optimal solutions using several randomly generated examples.
A Local Coordinate Approach in the MLPG Method for Beam Problems
NASA Technical Reports Server (NTRS)
Raju, Ivatury S.; Phillips, Dawn R.
2002-01-01
System matrices for Euler-Bernoulli beam problems for the meshless local Petrov-Galerkin (MLPG) method deteriorate as the number of nodes in the beam models are consistently increased. The reason for this behavior is explained. To overcome this difficulty and improve the accuracy of the solutions, a local coordinate approach for the evaluation of the generalized moving least squares shape functions and their derivatives is proposed. The proposed approach retains the accuracy of the MLPG methods.
Regularization of the circular restricted three-body problem using `similar' coordinate systems
NASA Astrophysics Data System (ADS)
Roman, R.; Szücs-Csillik, I.
2012-04-01
The regularization of a new problem, namely the three-body problem, using `similar' coordinate system is proposed. For this purpose we use the relation of `similarity', which has been introduced as an equivalence relation in a previous paper (see Roman in Astrophys. Space Sci. doi:10.1007/s10509-011-0747-1, 2011). First we write the Hamiltonian function, the equations of motion in canonical form, and then using a generating function, we obtain the transformed equations of motion. After the coordinates transformations, we introduce the fictitious time, to regularize the equations of motion. Explicit formulas are given for the regularization in the coordinate systems centered in the more massive and the less massive star of the binary system. The `similar' polar angle's definition is introduced, in order to analyze the regularization's geometrical transformation. The effect of Levi-Civita's transformation is described in a geometrical manner. Using the resulted regularized equations, we analyze and compare these canonical equations numerically, for the Earth-Moon binary system.
A multi-objective scatter search for a bi-criteria no-wait flow shop scheduling problem
NASA Astrophysics Data System (ADS)
Rahimi-Vahed, A. R.; Javadi, B.; Rabbani, M.; Tavakkoli-Moghaddam, R.
2008-04-01
The flow shop problem as a typical manufacturing challenge has gained wide attention in academic fields. This article considers a bi-criteria no-wait flow shop scheduling problem (FSSP) in which weighted mean completion time and weighted mean tardiness are to be minimized simultaneously. Since a FSSP has been proved to be NP-hard in a strong sense, a new multi-objective scatter search (MOSS) is designed for finding the locally Pareto-optimal frontier of the problem. To prove the efficiency of the proposed algorithm, various test problems are solved and the reliability of the proposed algorithm, based on some comparison metrics, is compared with a distinguished multi-objective genetic algorithm (GA), i.e. SPEA-II. The computational results show that the proposed MOSS performs better than the above GA, especially for the large-sized problems.
Personalized Education; Solving a Group Formation and Scheduling Problem for Educational Content
ERIC Educational Resources Information Center
Bahargam, Sanaz; Erdos, Dóra; Bestavros, Azer; Terzi, Evimaria
2015-01-01
Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1) group students so that they can maximally benefit from peer interaction and (2) find an optimal schedule of the educational…
NASA Technical Reports Server (NTRS)
Gaspin, Christine
1989-01-01
How a neural network can work, compared to a hybrid system based on an operations research and artificial intelligence approach, is investigated through a mission scheduling problem. The characteristic features of each system are discussed.
A Study on Machine Maintenance Scheduling Using Distributed Cooperative Approach
NASA Astrophysics Data System (ADS)
Tsujibe, Akihisa; Kaihara, Toshiya; Fujii, Nobutada; Nonaka, Youichi
In this study, we propose a distributed cooperative scheduling method, and apply the method into a machine maintenance scheduling problem in re-entrant production systems. As one of the distributed cooperative scheduling methods, we focus on Lagrangian decomposition and coordination (LDC) method, and formulate the machine maintenance scheduling problem with LDC so as to improve computational efficiency by decomposing an original scheduling problem into several sub-problems. The derived solutions by solving the decomposed dual problem are converted into feasible solutions with a heuristic procedure applied in this study. The proposed approach regards maintenance as job with starting and finishing time constraints, so that product and maintenance schedule can realize proper maintenance operations without losing productivity. We show the effectiveness of the proposed method in several simulation experiments.
NASA Astrophysics Data System (ADS)
Liou, Cheng-Dar; Hsieh, Yi-Chih; Chen, Yin-Yann
2013-01-01
This article investigates the two-machine flow-shop group scheduling problem (GSP) with sequence-dependent setup and removal times, and job transportation times between machines. The objective is to minimise the total completion time. As known, this problem is an NP-hard problem and generalises the typical two-machine GSPs. In this article, a new encoding scheme based on permutation representation is proposed to transform a random job permutation to a feasible permutation for GSPs. The proposed encoding scheme simultaneously determines both the sequence of jobs in each group and the sequence of groups. By reasonably combining particle swarm optimisation (PSO) and genetic algorithm (GA), we develop a fast and easily implemented hybrid algorithm (HA) for solving the considered problems. The effectiveness and efficiency of the proposed HA are demonstrated and compared with those of standard PSO and GA by numerical results of various tested instances with group numbers up to 20. In addition, three different lower bounds are developed to evaluate the solution quality of the HA. Limited numerical results indicate that the proposed HA is a viable and effective approach for the studied two-machine flow-shop group scheduling problem.
NASA Astrophysics Data System (ADS)
Bai, Danyu
2015-08-01
This paper discusses the flow shop scheduling problem to minimise the total quadratic completion time (TQCT) with release dates in offline and online environments. For this NP-hard problem, the investigation is focused on the performance of two online algorithms based on the Shortest Processing Time among Available jobs rule. Theoretical results indicate the asymptotic optimality of the algorithms as the problem scale is sufficiently large. To further enhance the quality of the original solutions, the improvement scheme is provided for these algorithms. A new lower bound with performance guarantee is provided, and computational experiments show the effectiveness of these heuristics. Moreover, several results of the single-machine TQCT problem with release dates are also obtained for the deduction of the main theorem.
NASA Astrophysics Data System (ADS)
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2013-12-01
In this article, an effective shuffled frog-leaping algorithm (SFLA) is proposed to solve the hybrid flow-shop scheduling problem with identical parallel machines (HFSP-IPM). First, some novel heuristic decoding rules for both job order decision and machine assignment are proposed. Then, three hybrid decoding schemes are designed to decode job order sequences to schedules. A special bi-level crossover and multiple local search operators are incorporated in the searching framework of the SFLA to enrich the memetic searching behaviour and to balance the exploration and exploitation capabilities. Meanwhile, some theoretical analysis for the local search operators is provided for guiding the local search. The parameter setting of the algorithm is also investigated based on the Taguchi method of design of experiments. Finally, numerical testing based on well-known benchmarks and comparisons with some existing algorithms are carried out to demonstrate the effectiveness of the proposed algorithm.
NASA Astrophysics Data System (ADS)
Wang, Hongfeng; Fu, Yaping; Huang, Min; Wang, Junwei
2016-03-01
The operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances.
Exploring the separability of the three-body Coulomb problem in hyperspherical elliptic coordinates
NASA Astrophysics Data System (ADS)
Tolstikhin, Oleg I.; Matsuzawa, Michio
2001-06-01
An approximate symmetry of the three-body Coulomb problem which reveals itself via approximate separability of the hyperspherical adiabatic (HSA) eigenvalue problem in hyperspherical elliptic (HSE) coordinates (η,ξ) and thus is intimately related to the HSA approximation is discussed. The additional integral of motion responsible for this separability is specific to the Coulomb interaction and generalizes the Laplace-Runge-Lentz vector known from the two-body Coulomb problem and the integral of separation constant of the two-center Coulomb problem. In the zeroth approximation, this symmetry leads to a completely separable representation of the three-body wave function, where each state is labeled by a pair of HSE quantum numbers (nη,nξ) that generalize the spheroidal quantum numbers for diatomic molecules, on the one hand, and the Herrick-Lin quantum numbers for two-electron atoms, on the other. This approximation is illustrated by calculations for a number of three-body Coulomb systems for states with zero total angular momentum. Taking into account the nonadiabatic couplings as well as the nonseparable part of the Coulomb potential by mixing a few separable states permits one to obtain accurate results for systems with arbitrary masses and charges of particles and for a wide spectrum below the three-body breakup threshold.
NASA Technical Reports Server (NTRS)
Lee, Paul U.; Smith, Nancy M.; Bienert, Nancy; Brasil, Connie; Buckley, Nathan; Chevalley, Eric; Homola, Jeffrey; Omar, Faisal; Parke, Bonny; Yoo, Hyo-Sang
2016-01-01
LaGuardia (LGA) departure delay was identified by the stakeholders and subject matter experts as a significant bottleneck in the New York metropolitan area. Departure delay at LGA is primarily due to dependency between LGA's arrival and departure runways: LGA departures cannot begin takeoff until arrivals have cleared the runway intersection. If one-in one-out operations are not maintained and a significant arrival-to-departure imbalance occurs, the departure backup can persist through the rest of the day. At NASA Ames Research Center, a solution called "Departure-sensitive Arrival Spacing" (DSAS) was developed to maximize the departure throughput without creating significant delays in the arrival traffic. The concept leverages a Terminal Sequencing and Spacing (TSS) operations that create and manage the arrival schedule to the runway threshold and added an interface enhancement to the traffic manager's timeline to provide the ability to manually adjust inter-arrival spacing to build precise gaps for multiple departures between arrivals. A more complete solution would include a TSS algorithm enhancement that could automatically build these multi-departure gaps. With this set of capabilities, inter-arrival spacing could be controlled for optimal departure throughput. The concept was prototyped in a human-in-the- loop (HITL) simulation environment so that operational requirements such as coordination procedures, timing and magnitude of TSS schedule adjustments, and display features for Tower, TRACON and Traffic Management Unit could be determined. A HITL simulation was conducted in August 2014 to evaluate the concept in terms of feasibility, controller workload impact, and potential benefits. Three conditions were tested, namely a Baseline condition without scheduling, TSS condition that schedules the arrivals to the runway threshold, and TSS+DSAS condition that adjusts the arrival schedule to maximize the departure throughput. The results showed that during high
NASA Astrophysics Data System (ADS)
Han, Yu-Yan; Gong, Dunwei; Sun, Xiaoyan
2015-07-01
A flow-shop scheduling problem with blocking has important applications in a variety of industrial systems but is underrepresented in the research literature. In this study, a novel discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE). The proposed algorithm (DE-ABC) contains three key operators. One is related to the employed bee operator (i.e. adopting mutation and crossover operators of discrete DE to generate solutions with good quality); the second is concerned with the onlooker bee operator, which modifies the selected solutions using insert or swap operators based on the self-adaptive strategy; and the last is for the local search, that is, the insert-neighbourhood-based local search with a small probability is adopted to improve the algorithm's capability in exploitation. The performance of the proposed DE-ABC algorithm is empirically evaluated by applying it to well-known benchmark problems. The experimental results show that the proposed algorithm is superior to the compared algorithms in minimizing the makespan criterion.
NASA Astrophysics Data System (ADS)
Basri, Azyanzuhaila Hasan; Zainuddin, Zaitul Marlizawati
2014-09-01
High efficiency of port operation is required to succeed in the competition between port container terminals. Berth Allocation and Quay Crane Scheduling are the most important part in container terminal operations. The integrated model is formulated as a MIP problem with the objective to minimize the sum of the dwell times, where a vessel's dwell time is measured between arrival and departure including both times waiting to be berthed and servicing time while berthed. The construction of suitable mathematical model is formulated by considering various practical constraints.
Germain, Shawn St; Farris, Ronald; Whaley, April M; Medema, Heather; Gertman, David
2014-09-01
This research effort is a part of the Light-Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by Department of Energy (DOE) and performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long-term, safe, and economical operation of current nuclear power plants. The LWRS program serves to help the U.S. nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. Managing NPP outages is a complex and difficult task due to the large number of maintenance and repair activities that are accomplished in a short period of time. During an outage, the outage control center (OCC) is the temporary command center for outage managers and provides several critical functions for the successful execution of the outage schedule. Essentially, the OCC functions to facilitate information inflow, assist outage management in processing information, and to facilitate the dissemination of information to stakeholders. Currently, outage management activities primarily rely on telephone communication, face to face reports of status, and periodic briefings in the OCC. It is a difficult task to maintain current the information related to outage progress and discovered conditions. Several advanced communication and collaboration technologies have shown promise for facilitating the information flow into, across, and out of the OCC. The use of these technologies will allow information to be shared electronically, providing greater amounts of real-time information to the decision makers and allowing OCC coordinators to meet with supporting staff remotely. Passively monitoring status electronically through advances in the areas of mobile worker technologies, computer-based procedures, and automated work packages will reduce the current reliance on manually
Agnetis, Alessandro; Coppi, Alberto; Corsini, Matteo; Dellino, Gabriella; Meloni, Carlo; Pranzo, Marco
2014-03-01
This research aims at supporting hospital management in making prompt Operating Room (OR) planning decisions, when either unpredicted events occur or alternative scenarios or configurations need to be rapidly evaluated. We design and test a planning tool enabling managers to efficiently analyse several alternatives to the current OR planning and scheduling. To this aim, we propose a decomposition approach. More specifically, we first focus on determining the Master Surgical Schedule (MSS) on a weekly basis, by assigning the different surgical disciplines to the available sessions. Next, we allocate surgeries to each session, focusing on elective patients only. Patients are selected from the waiting lists according to several parameters, including surgery duration, waiting time and priority class of the operations. We performed computational experiments to compare the performance of our decomposition approach with an (exact) integrated approach. The case study selected for our simulations is based on the characteristics of the operating theatre (OT) of a medium-size public Italian hospital. Scalability of the method is tested for different OT sizes. A pilot example is also proposed to highlight the usefulness of our approach for decision support. The proposed decomposition approach finds satisfactory solutions with significant savings in computation time. PMID:23783452
Learning to integrate reactivity and deliberation in uncertain planning and scheduling problems
NASA Technical Reports Server (NTRS)
Chien, Steve A.; Gervasio, Melinda T.; Dejong, Gerald F.
1992-01-01
This paper describes an approach to planning and scheduling in uncertain domains. In this approach, a system divides a task on a goal by goal basis into reactive and deliberative components. Initially, a task is handled entirely reactively. When failures occur, the system changes the reactive/deliverative goal division by moving goals into the deliberative component. Because our approach attempts to minimize the number of deliberative goals, we call our approach Minimal Deliberation (MD). Because MD allows goals to be treated reactively, it gains some of the advantages of reactive systems: computational efficiency, the ability to deal with noise and non-deterministic effects, and the ability to take advantage of unforseen opportunities. However, because MD can fall back upon deliberation, it can also provide some of the guarantees of classical planning, such as the ability to deal with complex goal interactions. This paper describes the Minimal Deliberation approach to integrating reactivity and deliberation and describe an ongoing application of the approach to an uncertain planning and scheduling domain.
The study of atomic three-body problems in hyperspherical coordinates
Lin, C.D.
1985-08-01
In this review the application of hyperspherical coordinates is discussed for the solution of some of the typical atomic and molecular problems, and the new physical insights obtained from such studies are shown. In particular, it is shown how correlations between two excited electrons can be conveniently understood in terms of the surface harmonics at a constant hyperradius and visualized by displaying the surface charge densities on the angular coordinates that describe radial and angular correlations. It is shown that a new set of correlation quantum numbers K, T and A for any two-electron states can be deduced by analyzing the surface harmonics; here K and T describe angular correlation and A = +1, -1 or 0) describes radial correlation. Because of the isomorphic correlations, states which have A = +1 or -1 are shown to exhibit supermultiplet structure while states which have A = 0 are shown to behave like singly excited states. Therefore this classification scheme includes the independent particle approximation as a subset. The relations of these quantum numbers to the collective vibrations and rotations of molecule-like normal modes are also discussed. Applications of hyperspherical harmonics to the three-body breakup and linear triatomic collisions are also discussed briefly. 57 refs., 15 figs.
NASA Astrophysics Data System (ADS)
Li, Jinsha; Li, Junmin
2016-07-01
In this paper, the adaptive fuzzy iterative learning control scheme is proposed for coordination problems of Mth order (M ≥ 2) distributed multi-agent systems. Every follower agent has a higher order integrator with unknown nonlinear dynamics and input disturbance. The dynamics of the leader are a higher order nonlinear systems and only available to a portion of the follower agents. With distributed initial state learning, the unified distributed protocols combined time-domain and iteration-domain adaptive laws guarantee that the follower agents track the leader uniformly on [0, T]. Then, the proposed algorithm extends to achieve the formation control. A numerical example and a multiple robotic system are provided to demonstrate the performance of the proposed approach.
NASA Technical Reports Server (NTRS)
Phillips, K.
1976-01-01
A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.
Numerical solution of flow problems using body-fitted coordinate systems
NASA Technical Reports Server (NTRS)
Thompson, J. F.
1980-01-01
The paper deals with numerically generated boundary-fitted coordinate systems. This procedure eliminates the shape of the boundaries as a complicating factor and allows the flow about arbitrary boundaries to be treated essentially as easily as that about simple boundaries. The technique of boundary-fitted coordinate systems is based on a method of automatic numerical generation of a general curvilinear coordinate system having a coordinate line coincident with each boundary of a general multiconnected region involving any number of arbitrarily shaped boundaries. Once the curvilinear coordinate system is generated, any partial differential system of interest may be solved on the coordinate system by transforming the equations and solving the resulting system in finite-difference approximation on the rectangular transformed plane. Attention is given to the types of boundary-fitted coordinate systems, coordinate system control, operation of the coordinate codes, solution of partial differential equations, application to free-surface flow, and other applications of interest.
NASA Astrophysics Data System (ADS)
Cram, Ana Catalina
As worldwide environmental awareness grow, alternative sources of energy have become important to mitigate climate change. Biogas in particular reduces greenhouse gas emissions that contribute to global warming and has the potential of providing 25% of the annual demand for natural gas in the U.S. In 2011, 55,000 metric tons of methane emissions were reduced and 301 metric tons of carbon dioxide emissions were avoided through the use of biogas alone. Biogas is produced by anaerobic digestion through the fermentation of organic material. It is mainly composed of methane with a rage of 50 to 80% in its concentration. Carbon dioxide covers 20 to 50% and small amounts of hydrogen, carbon monoxide and nitrogen. The biogas production systems are anaerobic digestion facilities and the optimal operation of an anaerobic digester requires the scheduling of all batches from multiple feedstocks during a specific time horizon. The availability times, biomass quantities, biogas production rates and storage decay rates must all be taken into account for maximal biogas production to be achieved during the planning horizon. Little work has been done to optimize the scheduling of different types of feedstock in anaerobic digestion facilities to maximize the total biogas produced by these systems. Therefore, in the present thesis, a new genetic algorithm is developed with the main objective of obtaining the optimal sequence in which different feedstocks will be processed and the optimal time to allocate to each feedstock in the digester with the main objective of maximizing the production of biogas considering different types of feedstocks, arrival times and decay rates. Moreover, all batches need to be processed in the digester in a specified time with the restriction that only one batch can be processed at a time. The developed algorithm is applied to 3 different examples and a comparison with results obtained in previous studies is presented.
Integrated scheduling and resource management. [for Space Station Information System
NASA Technical Reports Server (NTRS)
Ward, M. T.
1987-01-01
This paper examines the problem of integrated scheduling during the Space Station era. Scheduling for Space Station entails coordinating the support of many distributed users who are sharing common resources and pursuing individual and sometimes conflicting objectives. This paper compares the scheduling integration problems of current missions with those anticipated for the Space Station era. It examines the facilities and the proposed operations environment for Space Station. It concludes that the pattern of interdependecies among the users and facilities, which are the source of the integration problem is well structured, allowing a dividing of the larger problem into smaller problems. It proposes an architecture to support integrated scheduling by scheduling efficiently at local facilities as a function of dependencies with other facilities of the program. A prototype is described that is being developed to demonstrate this integration concept.
The Block Scheduling Handbook.
ERIC Educational Resources Information Center
Queen, J. Allen
Block scheduling encourages increased comprehensive immersion into subject matter, improved teacher-student relationships, and decreased disciplinary problems. While block scheduling may offer many advantages, moving to a block schedule from conventional scheduling can be a major adjustment for both students and teachers. This guide is intended to…
NASA Technical Reports Server (NTRS)
Richards, Stephen F.
1991-01-01
Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.
NASA Astrophysics Data System (ADS)
Yamamoto, Satoru
2005-07-01
A preconditioned flux-vector splitting (PFVS) scheme in general curvilinear coordinates which can be applied to condensate fluid and solid coupling problems is presented and some typical calculated results are shown to prove the availability of the present method. This method is based on the preconditioning method applied to compressible Navier-Stokes (NS) equations with additional equations and source terms for condensate flows. Since the present PFVS terms composed of the convective and pressure terms of the NS equations are completely reduced to only the pressure terms when the velocities are set to zero, the present scheme can further applied to the calculation not only for a dynamic field but also for a static field including a transitional field from the dynamic region to the static region. In this paper, as a first stage of the present study, coupling problems between a condensate flow in a flow field and heat conduction in a solid structure are simultaneously calculated by using the present method. As numerical examples, transonic and low speed flows around the NACA0012 airfoil, nonequilibrium condensate flows in a nozzle, and natural convection with condensation around a pipe at 1g and zero gravity are simulated with heat conduction in the solid structure.
Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support
NASA Technical Reports Server (NTRS)
Richards, Stephen F.
1992-01-01
The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.
Revealing hot executive function in children with motor coordination problems: What's the go?
Rahimi-Golkhandan, S; Steenbergen, B; Piek, J P; Caeyenberghs, K; Wilson, P H
2016-07-01
Recent research suggests that children with Developmental Coordination Disorder (DCD) often show deficits in executive functioning (EF) and, more specifically, the ability to use inhibitory control in 'hot', emotionally rewarding contexts. This study optimized the assessment of sensitivity of children with DCD to emotionally significant stimuli by using easily discriminable emotional expressions in a go/no-go task. Thirty-six children (12 with DCD), aged 7-12years, completed an emotional go/no-go task in which neutral facial expressions were paired with either happy or sad ones. Each expression was used as both, a go and no-go target in different runs of the task. There were no group differences in omission errors; however, the DCD group made significantly more commission errors to happy no-go faces. The particular pattern of performance in DCD confirms earlier reports of (hot) EF deficits. Specifically, a problem of inhibitory control appears to underlie the atypical pattern of performance seen in DCD on both cold and hot EF tasks. Disrupted coupling between cognitive control and emotion processing networks, such as fronto-parietal and fronto-striatal networks, may contribute to reduced inhibitory control in DCD. The implications for a broader theoretical account of DCD are discussed, as are implications for intervention. PMID:27254817
NASA Technical Reports Server (NTRS)
Rash, James
2014-01-01
NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial
Non-clairvoyant Scheduling Games
NASA Astrophysics Data System (ADS)
Dürr, Christoph; Nguyen, Kim Thang
In a scheduling game, each player owns a job and chooses a machine to execute it. While the social cost is the maximal load over all machines (makespan), the cost (disutility) of each player is the completion time of its own job. In the game, players may follow selfish strategies to optimize their cost and therefore their behaviors do not necessarily lead the game to an equilibrium. Even in the case there is an equilibrium, its makespan might be much larger than the social optimum, and this inefficiency is measured by the price of anarchy - the worst ratio between the makespan of an equilibrium and the optimum. Coordination mechanisms aim to reduce the price of anarchy by designing scheduling policies that specify how jobs assigned to a same machine are to be scheduled. Typically these policies define the schedule according to the processing times as announced by the jobs. One could wonder if there are policies that do not require this knowledge, and still provide a good price of anarchy. This would make the processing times be private information and avoid the problem of truthfulness. In this paper we study these so-called non-clairvoyant policies. In particular, we study the RANDOM policy that schedules the jobs in a random order without preemption, and the EQUI policy that schedules the jobs in parallel using time-multiplexing, assigning each job an equal fraction of CPU time.
The home health care routing and scheduling problem with interdependent services.
Mankowska, Dorota Slawa; Meisel, Frank; Bierwirth, Christian
2014-03-01
This paper presents a model for the daily planning of health care services carried out at patients' homes by staff members of a home care company. The planning takes into account individual service requirements of the patients, individual qualifications of the staff and possible interdependencies between different service operations. Interdependencies of services can include, for example, a temporal separation of two services as is required if drugs have to be administered a certain time before providing a meal. Other services like handling a disabled patient may require two staff members working together at a patient's home. The time preferences of patients are included in terms of given time windows. In this paper, we propose a planning approach for the described problem, which can be used for optimizing economical and service oriented measures of performance. A mathematical model formulation is proposed together with a powerful heuristic based on a sophisticated solution representation. PMID:23780750
Reinforcement learning in scheduling
NASA Technical Reports Server (NTRS)
Dietterich, Tom G.; Ok, Dokyeong; Zhang, Wei; Tadepalli, Prasad
1994-01-01
The goal of this research is to apply reinforcement learning methods to real-world problems like scheduling. In this preliminary paper, we show that learning to solve scheduling problems such as the Space Shuttle Payload Processing and the Automatic Guided Vehicle (AGV) scheduling can be usefully studied in the reinforcement learning framework. We discuss some of the special challenges posed by the scheduling domain to these methods and propose some possible solutions we plan to implement.
Integrated resource scheduling in a distributed scheduling environment
NASA Technical Reports Server (NTRS)
Zoch, David; Hall, Gardiner
1988-01-01
The Space Station era presents a highly-complex multi-mission planning and scheduling environment exercised over a highly distributed system. In order to automate the scheduling process, customers require a mechanism for communicating their scheduling requirements to NASA. A request language that a remotely-located customer can use to specify his scheduling requirements to a NASA scheduler, thus automating the customer-scheduler interface, is described. This notation, Flexible Envelope-Request Notation (FERN), allows the user to completely specify his scheduling requirements such as resource usage, temporal constraints, and scheduling preferences and options. The FERN also contains mechanisms for representing schedule and resource availability information, which are used in the inter-scheduler inconsistency resolution process. Additionally, a scheduler is described that can accept these requests, process them, generate schedules, and return schedule and resource availability information to the requester. The Request-Oriented Scheduling Engine (ROSE) was designed to function either as an independent scheduler or as a scheduling element in a network of schedulers. When used in a network of schedulers, each ROSE communicates schedule and resource usage information to other schedulers via the FERN notation, enabling inconsistencies to be resolved between schedulers. Individual ROSE schedules are created by viewing the problem as a constraint satisfaction problem with a heuristically guided search strategy.
NASA Astrophysics Data System (ADS)
Hasani, Keramat; Kravchenko, Svetlana A.; Werner, Frank
2016-01-01
This article considers the problem of scheduling a given set of n jobs on two identical parallel machines with a single server. Each job must be processed on one of the machines. Before processing, the server has to set up the relevant machine. The objective is to minimize the makespan. For this unary NP-hard problem, two fast constructive algorithms with a complexity of O(n2) are presented. The performance of these algorithms is evaluated for instances with up to 10,000 jobs. Computational results indicate that the algorithms have an excellent performance for very large instances so that the obtained objective function values are very close to a lower bound, and in many cases even an optimal solution is achieved. Superiority over all existing algorithms is obtained by sequencing the jobs on the two machines so that the machine idle time and the server waiting time are minimized. In doing so, the characteristics of an optimal solution resulting from its relevant lower bound are taken into account.
NASA Astrophysics Data System (ADS)
Kaplan, Sezgin; Rabadi, Ghaith
2013-01-01
This article addresses the aerial refuelling scheduling problem (ARSP), where a set of fighter jets (jobs) with certain ready times must be refuelled from tankers (machines) by their due dates; otherwise, they reach a low fuel level (deadline) incurring a high cost. ARSP is an identical parallel machine scheduling problem with release times and due date-to-deadline windows to minimize the total weighted tardiness. A simulated annealing (SA) and metaheuristic for randomized priority search (Meta-RaPS) with the newly introduced composite dispatching rule, apparent piecewise tardiness cost with ready times (APTCR), are applied to the problem. Computational experiments compared the algorithms' solutions to optimal solutions for small problems and to each other for larger problems. To obtain optimal solutions, a mixed integer program with a piecewise weighted tardiness objective function was solved for up to 12 jobs. The results show that Meta-RaPS performs better in terms of average relative error but SA is more efficient.
The Ames-Lockheed orbiter processing scheduling system
NASA Technical Reports Server (NTRS)
Zweben, Monte; Gargan, Robert
1991-01-01
A general purpose scheduling system and its application to Space Shuttle Orbiter Processing at the Kennedy Space Center (KSC) are described. Orbiter processing entails all the inspection, testing, repair, and maintenance necessary to prepare the Shuttle for launch and takes place within the Orbiter Processing Facility (OPF) at KSC, the Vehicle Assembly Building (VAB), and on the launch pad. The problems are extremely combinatoric in that there are thousands of tasks, resources, and other temporal considerations that must be coordinated. Researchers are building a scheduling tool that they hope will be an integral part of automating the planning and scheduling process at KSC. The scheduling engine is domain independent and is also being applied to Space Shuttle cargo processing problems as well as wind tunnel scheduling problems.
ERIC Educational Resources Information Center
Davis, Harold S.; Bechard, Joseph E.
A flexible schedule allows teachers to change group size, group composition, and class length according to the purpose of the lesson. This pamphlet presents various "master" schedules for flexible scheduling: (1) Simple block schedules, (2) back-to-back schedules, (3) interdisciplinary schedules, (4) school-wide block schedules, (5) open-lab…
NASA Technical Reports Server (NTRS)
Rash, James L.
2010-01-01
NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.
Parallel scheduling algorithms
Dekel, E.; Sahni, S.
1983-01-01
Parallel algorithms are given for scheduling problems such as scheduling to minimize the number of tardy jobs, job sequencing with deadlines, scheduling to minimize earliness and tardiness penalties, channel assignment, and minimizing the mean finish time. The shared memory model of parallel computers is used to obtain fast algorithms. 26 references.
NASA Astrophysics Data System (ADS)
Iñarrea, Manuel; Lanchares, Víctor; Palacián, Jesús F.; Pascual, Ana I.; Salas, J. Pablo; Yanguas, Patricia
In order to analyse the dynamics of a given Hamiltonian system in the space defined as the Cartesian product of two spheres, we propose to combine Delaunay coordinates with Poincaré-like coordinates. The coordinates are of local character and have to be selected accordingly with the type of motions one has to take into consideration, so we distinguish the following types: (i) rectilinear motions; (ii) circular and equatorial motions; (iii) circular non-equatorial motions; (iv) non-circular equatorial motions; and (v) non-circular and non-equatorial motions. We apply the theory to study the dynamics of the reduced flow of a generalised Størmer problem that is modelled as a perturbation of the Kepler problem. After using averaging and reduction theories, the corresponding flow is analysed on the manifold S×S, calculating the occurring equilibria and their stability. Finally, the flow of the original problem is reconstructed, concluding the existence of some families of periodic solutions and KAM tori.
Preventing Alcohol-Related Problems on Campus: Acquaintance Rape. A Guide for Program Coordinators.
ERIC Educational Resources Information Center
Finn, Peter
This is a guide for college and university program coordinators and planning committees on how to establish, expand, or improve a program on the prevention of acquaintance rape. Information is given for Presidents, Vice Presidents, and Deans on the relationship between acquaintance rape and alcohol, reasons for top administrators to become…
Analyzing Group Coordination when Solving Geometry Problems with Dynamic Geometry Software
ERIC Educational Resources Information Center
Oner, Diler
2013-01-01
In CSCL research, collaborative activity is conceptualized along various yet intertwined dimensions. When functioning within these multiple dimensions, participants make use of several resources, which can be social or content-related (and sometimes temporal) in nature. It is the effective coordination of these resources that appears to…
Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems
Scherrer, Chad; Halappanavar, Mahantesh; Tewari, Ambuj; Haglin, David J.
2012-07-03
We present a generic framework for parallel coordinate descent (CD) algorithms that has as special cases the original sequential algorithms of Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm of Bradley et al. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and Coloring-Based CD---and give performance measurements for an OpenMP implementation of these.
Tao, Liang; McCurdy, C.W.; Rescigno, T.N.
2008-11-25
We show how to combine finite elements and the discrete variable representation in prolate spheroidal coordinates to develop a grid-based approach for quantum mechanical studies involving diatomic molecular targets. Prolate spheroidal coordinates are a natural choice for diatomic systems and have been used previously in a variety of bound-state applications. The use of exterior complex scaling in the present implementation allows for a transparently simple way of enforcing Coulomb boundary conditions and therefore straightforward application to electronic continuum problems. Illustrative examples involving the bound and continuum states of H2+, as well as the calculation of photoionization cross sections, show that the speed and accuracy of the present approach offer distinct advantages over methods based on single-center expansions.
Investigations in the problem of pion condensation using generator co-ordinate methods
NASA Astrophysics Data System (ADS)
Chattopadhyay, P.; Da Providencia, J.
1981-11-01
Pion condensation in neutron matter has been investigated using the generator coordinate method and a simple p-wave interaction. The assumption of a condensed mode corresponding to one pion momentum (determined variationally) helps evaluate all the necessary matrix elements exactly. The technique of charge projection from a coherent state of negative pions is discussed, and calculations have been carried out for the cases of average charge conservation, charge projection before variation and for a charge conserving trial function. The ground-state energies and the lowest excitations of the system are obtained from numerical solutions of the Hill-Wheeler equation.
Scheduling Jobs with Genetic Algorithms
NASA Astrophysics Data System (ADS)
Ferrolho, António; Crisóstomo, Manuel
Most scheduling problems are NP-hard, the time required to solve the problem optimally increases exponentially with the size of the problem. Scheduling problems have important applications, and a number of heuristic algorithms have been proposed to determine relatively good solutions in polynomial time. Recently, genetic algorithms (GA) are successfully used to solve scheduling problems, as shown by the growing numbers of papers. GA are known as one of the most efficient algorithms for solving scheduling problems. But, when a GA is applied to scheduling problems various crossovers and mutations operators can be applicable. This paper presents and examines a new concept of genetic operators for scheduling problems. A software tool called hybrid and flexible genetic algorithm (HybFlexGA) was developed to examine the performance of various crossover and mutation operators by computing simulations of job scheduling problems.
A note on problems in 3D boundary layer computations in streamline coordinates
NASA Astrophysics Data System (ADS)
Scholtysik, M.; Bettelini, M.; Fanneløp, T. K.
1994-01-01
Turbulent boundary layers with convergent and divergent external streamlines over a flat plate in the neighbourhood of a plane of symmetry have been computed using a finite-difference method based on streamline coordinates. While the results for the divergent case are generally satisfactory, error growth has been observed for the convergent flowfield. This is most pronounced near the lateral boundary of the computational domain, but also occurs in the plane of symmetry. As an ad-hoc engineering solution, a modified and more restrictive definition of the domain of dependence is proposed, which eliminates the part of the computational domain where the largest error growth occurs. The observed tendency to instability in the convergent case is confirmed by a simplified stability analysis after von Neumann of the uncoupled governing equations.
Preventing Alcohol-Related Problems on Campus: Impaired Driving. A Guide for Program Coordinators.
ERIC Educational Resources Information Center
DeJong, William
This guide presents detailed descriptions of potentially effective approaches to preventing impaired driving by college students due to alcohol abuse. Chapter 1 provides an overview of alcohol-impaired driving and discusses changes in public attitudes, the scope of the problem, involvement of teens and young adults, and the challenge of reaching…
A Comparison of Techniques for Scheduling Earth-Observing Satellites
NASA Technical Reports Server (NTRS)
Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna
2004-01-01
Scheduling observations by coordinated fleets of Earth Observing Satellites (EOS) involves large search spaces, complex constraints and poorly understood bottlenecks, conditions where evolutionary and related algorithms are often effective. However, there are many such algorithms and the best one to use is not clear. Here we compare multiple variants of the genetic algorithm: stochastic hill climbing, simulated annealing, squeaky wheel optimization and iterated sampling on ten realistically-sized EOS scheduling problems. Schedules are represented by a permutation (non-temperal ordering) of the observation requests. A simple deterministic scheduler assigns times and resources to each observation request in the order indicated by the permutation, discarding those that violate the constraints created by previously scheduled observations. Simulated annealing performs best. Random mutation outperform a more 'intelligent' mutator. Furthermore, the best mutator, by a small margin, was a novel approach we call temperature dependent random sampling that makes large changes in the early stages of evolution and smaller changes towards the end of search.
Jelsma, Dorothee; Geuze, Reint H; Mombarg, Remo; Smits-Engelsman, Bouwien C M
2014-02-01
The aim of this study was to examine differences in the performance of children with probable Developmental Coordination Disorder (p-DCD) and balance problems (BP) and typical developing children (TD) on a Wii Fit task and to measure the effect on balance skills after a Wii Fit intervention. Twenty-eight children with BP and 20 TD-children participated in the study. Motor performance was assessed with the Movement Assessment Battery for Children (MABC2), three subtests of the Bruininks Oseretsky Test (BOT2): Bilateral Coordination, Balance and Running Speed & Agility, and a Wii Fit ski slalom test. The TD children and half of the children in the BP group were tested before and after a 6weeks non-intervention period. All children with BP received 6weeks of Wii Fit intervention (with games other than the ski game) and were tested before and afterwards. Children with BP were less proficient than TD children in playing the Wii Fit ski slalom game. Training with the Wii Fit improved their motor performance. The improvement was significantly larger after intervention than after a period of non-intervention. Therefore the change cannot solely be attributed to spontaneous development or test-retest effect. Nearly all children enjoyed participation during the 6weeks of intervention. Our study shows that Wii Fit intervention is effective and is potentially a method to support treatment of (dynamic) balance control problems in children. PMID:24444657
van den Heuvel, Meta; Jansen, Danielle E M C; Reijneveld, Sijmen A; Flapper, Boudien C T; Smits-Engelsman, Bouwien C M
2016-01-01
Current evidence on the co-occurrence of Developmental Coordination Disorder (DCD) and psychosocial problems mainly concerns parent-reported information, but rarely includes teacher information. The aim of this study was (1) to investigate the teachers' identification of emotional and behavioral problems in children with DCD and (2) to examine the performance of the teacher version of the Strengths and Difficulties Questionnaire (SDQ-T) compared with the Teacher Report Form (TRF) in children with DCD. We assessed primary school children (202 boys, 200 girls, range 4-10.8 years, mean age 7.2 years) for DCD following the DSM IV-TR criteria. Emotional and behavioral problems were measured with the TRF (n=327) and the SDQ-T (n=361). DCD was established in 23 (5.7%) children, 16 boys and 7 girls (mean age 7.0 years). Children with DCD had a higher proportion of clinical scores on both the TRF Total Problem Scale (TRF TPS) and SDQ-T Total Difficulties Score (SDQ-T TDS). Children with DCD had increased odds on the TRF domains Thought (odds ratio, OR: 5.39), Externalizing (OR: 4.12) and Internalizing (OR: 4.42) problems, and on all SDQ-T-domains and Total Difficulties score (OR: 7.30). In the DCD group the SDQ-T TDS correlated strongly (Spearman's rho 0.80) with the TRF TPS and demonstrated a moderate agreement (Cohen's Kappa 0.53). In conclusion, teachers identified significantly more emotional and behavioral problems in children with DCD compared with their peers. The SDQ-T showed moderate agreement with the TRF in identifying emotional and behavioral problems in children with DCD. PMID:26780353
NASA Technical Reports Server (NTRS)
Messing, Fredric
1993-01-01
This paper provides an analytical formulation to predict scheduling success for a class of problems frequently referred to as activity scheduling. Space Network communications scheduling is an example of activity scheduling. The principal assumption is that the activity start times are randomly distributed over the available time in the time line. The formulation makes it possible to estimate how much of the demand can be scheduled as a function of the demand, number of resources, activity duration, and activity flexibility. The paper includes computed results for a variety of resource and demand conditions. The results demonstrate that even with highly flexible activities, it is difficult to schedule demand greater than 60 percent of resources without the use of optimization and conflict resolution capabilities in the scheduling system.
Automated Scheduling Via Artificial Intelligence
NASA Technical Reports Server (NTRS)
Biefeld, Eric W.; Cooper, Lynne P.
1991-01-01
Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.
Scheduling Earth Observing Satellites with Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna
2003-01-01
We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.
Whitley, L. Darrell; Watson, Jean-Paul; Howe, Adele E.
2005-06-01
Over the last decade and a half, tabu search algorithms for machine scheduling have gained a near-mythical reputation by consistently equaling or establishing state-of-the-art performance levels on a range of academic and real-world problems. Yet, despite these successes, remarkably little research has been devoted to developing an understanding of why tabu search is so effective on this problem class. In this paper, we report results that provide significant progress in this direction. We consider Nowicki and Smutnicki's i-TSAB tabu search algorithm, which represents the current state-of-the-art for the makespan-minimization form of the classical jobshop scheduling problem. Via a series of controlled experiments, we identify those components of i-TSAB that enable it to achieve state-of-the-art performance levels. In doing so, we expose a number of misconceptions regarding the behavior and/or benefits of tabu search and other local search metaheuristics for the job-shop problem. Our results also serve to focus future research, by identifying those specific directions that are most likely to yield further improvements in performance.
NASA Technical Reports Server (NTRS)
Wang, Yeou-Fang; Baldwin, John
2007-01-01
TIGRAS is client-side software, which provides tracking-station equipment planning, allocation, and scheduling services to the DSMS (Deep Space Mission System). TIGRAS provides functions for schedulers to coordinate the DSN (Deep Space Network) antenna usage time and to resolve the resource usage conflicts among tracking passes, antenna calibrations, maintenance, and system testing activities. TIGRAS provides a fully integrated multi-pane graphical user interface for all scheduling operations. This is a great improvement over the legacy VAX VMS command line user interface. TIGRAS has the capability to handle all DSN resource scheduling aspects from long-range to real time. TIGRAS assists NASA mission operations for DSN tracking of station equipment resource request processes from long-range load forecasts (ten years or longer), to midrange, short-range, and real-time (less than one week) emergency tracking plan changes. TIGRAS can be operated by NASA mission operations worldwide to make schedule requests for the DSN station equipment.
Ostojić, Ljerka; Clayton, Nicola S
2014-03-01
The process of domestication has arguably provided dogs (Canis familiaris) with decreased emotional reactivity (reduced fear and aggression) and increased socio-cognitive skills adaptive for living with humans. It has been suggested that dogs are uniquely equipped with abilities that have been identified as crucial in cooperative problem-solving, namely social tolerance and the ability to attend to other individuals' behaviour. Accordingly, dogs might be hypothesised to perform well in tasks in which they have to work together with a human partner. Recently, researchers have found that dogs successfully solved a simple cooperative task with another dog. Due to the simplicity of the task, this study was, however, unable to provide clear evidence as to whether the dogs' successful performance was based on the cognitive ability of behavioural coordination, namely the capacity to link task requirements to the necessity of adjusting one's actions to the partner's behaviour. Here, we tested dogs with the most commonly used cooperative task, appropriate to test behavioural coordination. In addition, we paired dogs with both a conspecific and a human partner. Although dogs had difficulties in inhibiting the necessary action when required to wait for their partner, they successfully attended to the two cues that predicted a successful outcome, namely their partner's behaviour and the incremental movement of rewards towards themselves. This behavioural coordination was shown with both a conspecific and a human partner, in line with the recent findings suggesting that dogs exhibit highly developed socio-cognitive skills in interactions with both humans and other dogs. PMID:23995845
Constrained Task Assignment and Scheduling On Networks of Arbitrary Topology
NASA Astrophysics Data System (ADS)
Jackson, Justin Patrick
This dissertation develops a framework to address centralized and distributed constrained task assignment and task scheduling problems. This framework is used to prove properties of these problems that can be exploited, develop effective solution algorithms, and to prove important properties such as correctness, completeness and optimality. The centralized task assignment and task scheduling problem treated here is expressed as a vehicle routing problem with the goal of optimizing mission time subject to mission constraints on task precedence and agent capability. The algorithm developed to solve this problem is able to coordinate vehicle (agent) timing for task completion. This class of problems is NP-hard and analytical guarantees on solution quality are often unavailable. This dissertation develops a technique for determining solution quality that can be used on a large class of problems and does not rely on traditional analytical guarantees. For distributed problems several agents must communicate to collectively solve a distributed task assignment and task scheduling problem. The distributed task assignment and task scheduling algorithms developed here allow for the optimization of constrained military missions in situations where the communication network may be incomplete and only locally known. Two problems are developed. The distributed task assignment problem incorporates communication constraints that must be satisfied; this is the Communication-Constrained Distributed Assignment Problem. A novel distributed assignment algorithm, the Stochastic Bidding Algorithm, solves this problem. The algorithm is correct, probabilistically complete, and has linear average-case time complexity. The distributed task scheduling problem addressed here is to minimize mission time subject to arbitrary predicate mission constraints; this is the Minimum-time Arbitrarily-constrained Distributed Scheduling Problem. The Optimal Distributed Non-sequential Backtracking Algorithm
Completable scheduling: An integrated approach to planning and scheduling
NASA Technical Reports Server (NTRS)
Gervasio, Melinda T.; Dejong, Gerald F.
1992-01-01
The planning problem has traditionally been treated separately from the scheduling problem. However, as more realistic domains are tackled, it becomes evident that the problem of deciding on an ordered set of tasks to achieve a set of goals cannot be treated independently of the problem of actually allocating resources to the tasks. Doing so would result in losing the robustness and flexibility needed to deal with imperfectly modeled domains. Completable scheduling is an approach which integrates the two problems by allowing an a priori planning module to defer particular planning decisions, and consequently the associated scheduling decisions, until execution time. This allows a completable scheduling system to maximize plan flexibility by allowing runtime information to be taken into consideration when making planning and scheduling decision. Furthermore, through the criteria of achievability placed on deferred decision, a completable scheduling system is able to retain much of the goal-directedness and guarantees of achievement afforded by a priori planning. The completable scheduling approach is further enhanced by the use of contingent explanation-based learning, which enables a completable scheduling system to learn general completable plans from example and improve its performance through experience. Initial experimental results show that completable scheduling outperforms classical scheduling as well as pure reactive scheduling in a simple scheduling domain.
NASA Astrophysics Data System (ADS)
Lai, Pik-Yin
Methods of statistical mechanics are applied to two important NP-complete combinatorial optimization problems. The first is the chromatic number problem which seeks the minimal number of colors necessary to color a graph such that no two sites connected by an edge have the same color. The second is partitioning of a graph into q equal subgraphs so as to minimize inter-subgraph connections. Both models are mapped into a frustrated Potts model which is related to the q-state Potts spin glass. For the first problem, we obtain very good agreement with numerical simulations and theoretical bounds using the annealed approximation. The quenched model is also discussed. For the second problem we obtain analytic and numerical results by evaluating the ground state energy of the q = 3 and 4 Potts spin glass using Parisi's replica symmetry breaking. We also performed some numerical simulations to test the theoretical result and obtained very good agreement. In the second part of the thesis, we simulate the Ising spin-glass model on a random lattice with a finite (average) coordination number and also on the Bethe lattice with various different boundary conditions. In particular, we calculate the overlap function P(q) for two independent samples. For the random lattice, the results are consistent with a spin-glass transition above which P(q) converges to a Dirac delta -function for large N (number of sites) and below which P(q) has in addition a long tail similar to previous results obtained for the infinite ranged model. For the Bethe lattice, we obtain results in the interior by discarding the two outer shells of the Cayley tree when calculating the thermal averages. For fixed (uncorrelated) boundary conditions, P(q) seems to converge to a delta -function even below the spin-glass transition whereas for a "closed" lattice (correlated boundary conditions) P(q) has a long tail similar to its behavior in the random lattice case.
NASA Technical Reports Server (NTRS)
Tanner, Steve; Hughes, Angi; Byrd, Jim
1987-01-01
Resupply scheduling for the Space Station presents some formidable logistics problems. One of the most basic problems is assigning supplies to a series of shuttle resupply missions. A prototype logistics expert system which constructs resupply schedules was developed. This prototype is able to reconstruct feasible resupply plans. In addition, analysts can use the system to evaluate the impact of adding, deleting or modifying launches, cargo space, experiments, etc.
Daveson, Barbara A.; Harding, Richard; Shipman, Cathy; Mason, Bruce L.; Epiphaniou, Eleni; Higginson, Irene J.; Ellis-Smith, Clare; Henson, Lesley; Munday, Dan; Nanton, Veronica; Dale, Jeremy R.; Boyd, Kirsty; Worth, Allison; Barclay, Stephen; Donaldson, Anne; Murray, Scott
2014-01-01
Objectives To develop a model of care coordination for patients living with advanced progressive illness and their unpaid caregivers, and to understand their perspective regarding care coordination. Design A prospective longitudinal, multi-perspective qualitative study involving a case-study approach. Methods Serial in-depth interviews were conducted, transcribed verbatim and then analyzed through open and axial coding in order to construct categories for three cases (sites). This was followed by continued thematic analysis to identify underlying conceptual coherence across all cases in order to produce one coherent care coordination model. Participants Fifty-six purposively sampled patients and 27 case-linked unpaid caregivers. Settings Three cases from contrasting primary, secondary and tertiary settings within Britain. Results Coordination is a deliberate cross-cutting action that involves high-quality, caring and well-informed staff, patients and unpaid caregivers who must work in partnership together across health and social care settings. For coordination to occur, it must be adequately resourced with efficient systems and services that communicate. Patients and unpaid caregivers contribute substantially to the coordination of their care, which is sometimes volunteered at a personal cost to them. Coordination is facilitated through flexible and patient-centered care, characterized by accurate and timely information communicated in a way that considers patients’ and caregivers’ needs, preferences, circumstances and abilities. Conclusions Within the midst of advanced progressive illness, coordination is a shared and complex intervention involving relational, structural and information components. Our study is one of the first to extensively examine patients’ and caregivers’ views about coordination, thus aiding conceptual fidelity. These findings can be used to help avoid oversimplifying a real-world problem, such as care coordination. Avoiding
State-based scheduling: An architecture for telescope observation scheduling
NASA Technical Reports Server (NTRS)
Muscettola, Nicola; Smith, Stephen F.
1989-01-01
The applicability of constraint-based scheduling, a methodology previously developed and validated in the domain of factory scheduling, is extended to problem domains that require attendance to a wider range of state-dependent constraints. The problem of constructing and maintaining a short-term observation schedule for the Hubble Space Telescope (HST), which typifies this type of domain is the focus of interest. The nature of the constraints encountered in the HST domain is examined, system requirements are discussed with respect to utilization of a constraint-based scheduling methodology in such domains, and a general framework for state-based scheduling is presented.
... Labor & birth > Scheduling a c-section Scheduling a c-section E-mail to a friend Please fill ... develop before she’s born. Why can scheduling a c-section for non-medical reasons be a problem? ...
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
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
Adaptive Parallel Job Scheduling with Flexible CoScheduling
Frachtenberg, Eitan; Feitelson, Dror; Petrini, Fabrizio; Fernandez, Juan
2005-11-01
Abstract—Many scientific and high-performance computing applications consist of multiple processes running on different processors that communicate frequently. Because of their synchronization needs, these applications can suffer severe performance penalties if their processes are not all coscheduled to run together. Two common approaches to coscheduling jobs are batch scheduling, wherein nodes are dedicated for the duration of the run, and gang scheduling, wherein time slicing is coordinated across processors. Both work well when jobs are load-balanced and make use of the entire parallel machine. However, these conditions are rarely met and most realistic workloads consequently suffer from both internal and external fragmentation, in which resources and processors are left idle because jobs cannot be packed with perfect efficiency. This situation leads to reduced utilization and suboptimal performance. Flexible CoScheduling (FCS) addresses this problem by monitoring each job’s computation granularity and communication pattern and scheduling jobs based on their synchronization and load-balancing requirements. In particular, jobs that do not require stringent synchronization are identified, and are not coscheduled; instead, these processes are used to reduce fragmentation. FCS has been fully implemented on top of the STORM resource manager on a 256-processor Alpha cluster and compared to batch, gang, and implicit coscheduling algorithms. This paper describes in detail the implementation of FCS and its performance evaluation with a variety of workloads, including large-scale benchmarks, scientific applications, and dynamic workloads. The experimental results show that FCS saturates at higher loads than other algorithms (up to 54 percent higher in some cases), and displays lower response times and slowdown than the other algorithms in nearly all scenarios.
NASA Astrophysics Data System (ADS)
Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin
2016-03-01
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
NASA Schedule Management Handbook
NASA Technical Reports Server (NTRS)
2011-01-01
The purpose of schedule management is to provide the framework for time-phasing, resource planning, coordination, and communicating the necessary tasks within a work effort. The intent is to improve schedule management by providing recommended concepts, processes, and techniques used within the Agency and private industry. The intended function of this handbook is two-fold: first, to provide guidance for meeting the scheduling requirements contained in NPR 7120.5, NASA Space Flight Program and Project Management Requirements, NPR 7120.7, NASA Information Technology and Institutional Infrastructure Program and Project Requirements, NPR 7120.8, NASA Research and Technology Program and Project Management Requirements, and NPD 1000.5, Policy for NASA Acquisition. The second function is to describe the schedule management approach and the recommended best practices for carrying out this project control function. With regards to the above project management requirements documents, it should be noted that those space flight projects previously established and approved under the guidance of prior versions of NPR 7120.5 will continue to comply with those requirements until project completion has been achieved. This handbook will be updated as needed, to enhance efficient and effective schedule management across the Agency. It is acknowledged that most, if not all, external organizations participating in NASA programs/projects will have their own internal schedule management documents. Issues that arise from conflicting schedule guidance will be resolved on a case by case basis as contracts and partnering relationships are established. It is also acknowledged and understood that all projects are not the same and may require different levels of schedule visibility, scrutiny and control. Project type, value, and complexity are factors that typically dictate which schedule management practices should be employed.
ERIC Educational Resources Information Center
van Waelvelde, Hilde; Oostra, Ann; DeWitte, Griet; van den Broeck, Christine; Jongmans, Marian J.
2010-01-01
Aim: The aim of this study was to investigate the stability of motor problems in a clinically referred sample of children with, or at risk of, autism spectrum disorders (ASDs), attention-deficit-hyperactivity disorder (ADHD), and/or developmental coordination disorder (DCD). Method: Participants were 49 children (39 males, 10 females; mean age 5y…
Planning and Scheduling for Environmental Sensor Networks
NASA Astrophysics Data System (ADS)
Frank, J. D.
2005-12-01
resources and to reduce the costs of communication. Planning and scheduling is generally a heavy consumer of time, memory and energy resources. This means careful thought must be given to how much planning and scheduling should be done on the sensors themselves, and how much to do elsewhere. The difficulty of planning and scheduling is exacerbated when reasoning about uncertainty. More time, memory and energy is needed to solve such problems, leading either to more expensive sensors, or suboptimal plans. For example, scientifically interesting events may happen at random times, making it difficult to ensure that sufficient resources are availanble. Since uncertainty is usually lowest in proximity to the sensors themselves, this argues for planning and scheduling onboard the sensors. However, cost minimization dictates sensors be kept as simple as possible, reducing the amount of planning and scheduling they can do themselves. Furthermore, coordinating each sensor's independent plans can be difficult. In the full presentation, we will critically review the planning and scheduling systems used by previously fielded sensor networks. We do so primarily from the perspective of the computational sciences, with a focus on taming computational complexity when operating sensor networks. The case studies are derived from sensor networks based on UAVs, satellites, and planetary rovers. Planning and scheduling considerations include multi-sensor coordination, optimizing science value, onboard power management, onboard memory, planning movement actions to acquire data, and managing communications.These case studies offer lessons for future designs of environmental sensor networks.
Artificial intelligence approaches to astronomical observation scheduling
NASA Technical Reports Server (NTRS)
Johnston, Mark D.; Miller, Glenn
1988-01-01
Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.
Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.
2015-01-01
Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406
Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M K
2015-01-01
Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406
DTS: Building custom, intelligent schedulers
NASA Technical Reports Server (NTRS)
Hansson, Othar; Mayer, Andrew
1994-01-01
DTS is a decision-theoretic scheduler, built on top of a flexible toolkit -- this paper focuses on how the toolkit might be reused in future NASA mission schedulers. The toolkit includes a user-customizable scheduling interface, and a 'Just-For-You' optimization engine. The customizable interface is built on two metaphors: objects and dynamic graphs. Objects help to structure problem specifications and related data, while dynamic graphs simplify the specification of graphical schedule editors (such as Gantt charts). The interface can be used with any 'back-end' scheduler, through dynamically-loaded code, interprocess communication, or a shared database. The 'Just-For-You' optimization engine includes user-specific utility functions, automatically compiled heuristic evaluations, and a postprocessing facility for enforcing scheduling policies. The optimization engine is based on BPS, the Bayesian Problem-Solver (1,2), which introduced a similar approach to solving single-agent and adversarial graph search problems.
Kleck, W
1982-04-01
Structuring a schedule - whether by Critical Path Method (CPM) or Precedence Charting System (PCS) - involves estimating the duration of one or more activities and arranging them in the most logical sequence. Given the start date, the completion date is relatively simple to determine. What is then so complicated about the process. It is complicated by the people involved - the people who make the schedules and the people who attempt to follow them. Schedules are an essential part of project management and construction contract administration. Much of the material available pertains to the mechanics of schedules, the types of logic networks, the ways that data can be generated and presented. This paper sheds light on other facets of the subject - the statistical and philosophical fundamentals involved in scheduling.
Automated Platform Management System Scheduling
NASA Technical Reports Server (NTRS)
Hull, Larry G.
1990-01-01
The Platform Management System was established to coordinate the operation of platform systems and instruments. The management functions are split between ground and space components. Since platforms are to be out of contact with the ground more than the manned base, the on-board functions are required to be more autonomous than those of the manned base. Under this concept, automated replanning and rescheduling, including on-board real-time schedule maintenance and schedule repair, are required to effectively and efficiently meet Space Station Freedom mission goals. In a FY88 study, we developed several promising alternatives for automated platform planning and scheduling. We recommended both a specific alternative and a phased approach to automated platform resource scheduling. Our recommended alternative was based upon use of exactly the same scheduling engine in both ground and space components of the platform management system. Our phased approach recommendation was based upon evolutionary development of the platform. In the past year, we developed platform scheduler requirements and implemented a rapid prototype of a baseline platform scheduler. Presently we are rehosting this platform scheduler rapid prototype and integrating the scheduler prototype into two Goddard Space Flight Center testbeds, as the ground scheduler in the Scheduling Concepts, Architectures, and Networks Testbed and as the on-board scheduler in the Platform Management System Testbed. Using these testbeds, we will investigate rescheduling issues, evaluate operational performance and enhance the platform scheduler prototype to demonstrate our evolutionary approach to automated platform scheduling. The work described in this paper was performed prior to Space Station Freedom rephasing, transfer of platform responsibility to Code E, and other recently discussed changes. We neither speculate on these changes nor attempt to predict the impact of the final decisions. As a consequence some of our
NASA Technical Reports Server (NTRS)
Zweben, Monte
1991-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocations for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its applications to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
NASA Technical Reports Server (NTRS)
Zweben, Monte
1991-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
NASA Technical Reports Server (NTRS)
Zweben, Monte
1993-01-01
The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.
Enhanced Memetic Algorithm for Task Scheduling
NASA Astrophysics Data System (ADS)
Padmavathi, S.; Shalinie, S. Mercy; Someshwar, B. C.; Sasikumar, T.
Scheduling tasks onto the processors of a parallel system is a crucial part of program parallelization. Due to the NP-hardness of the task scheduling problem, scheduling algorithms are based on heuristics that try to produce good rather than optimal schedules. This paper proposes a Memetic algorithm with Tabu search and Simulated Annealing as local search for solving Task scheduling problem considering communication contention. This problem consists of finding a schedule for a general task graph to be executed on a cluster of workstations and hence the schedule length can be minimized. Our approach combines local search (by self experience) and global search (by neighboring experience) possessing high search efficiency. The proposed approach is compared with existing list scheduling heuristics. The numerical results clearly indicate that our proposed approach produces solutions which are closer to optimality and/or better quality than the existing list scheduling heuristics.
ERIC Educational Resources Information Center
Berteotti, Carol R.; And Others
Using an evaluation of a hospital-based hospice as a case study, this paper analyzes problematic issues surrounding health care teams (HCTs) in light of findings revealed in the literature concerning HCT structures and processes. The factors of coordination and role definitions in HCTs and their manifestations in a particular hospice HCT in terms…
Training and Operations Integrated Calendar Scheduler - TROPICS
J.E. Oppenlander; A.J. Levy; V.A. Arbige; A.H. Shoop
2003-01-27
TROPICS is a rule-based scheduling system that optimizes the training experience for students in a power (note this change should be everywhere, i.e. Not reactor) plant environment. The problem is complicated by the condition that plant resources and users' time must be simultaneously scheduled to make best use of both. The training facility is highly constrained in how it is used, and, as in many similar environments, subject to dynamic change with little or no advance notice. The flexibility required extends to changes resulting from students' actions such as absences. Even though the problem is highly constrained by plant usage and student objectives, the large number of possible schedules is a concern. TROPICS employs a control strategy for rule firing to prune the possibility tree and avoid combinatorial explosion. The application has been in use since 1996, first as a prototype for testing and then in production. Training Coordinators have a philosophical aspect to teaching students that has made the rule-based approach much more verifiable and satisfying to the domain experts than other forms of capturing expertise.
Scheduling: A guide for program managers
NASA Technical Reports Server (NTRS)
1994-01-01
The following topics are discussed concerning scheduling: (1) milestone scheduling; (2) network scheduling; (3) program evaluation and review technique; (4) critical path method; (5) developing a network; (6) converting an ugly duckling to a swan; (7) network scheduling problem; (8) (9) network scheduling when resources are limited; (10) multi-program considerations; (11) influence on program performance; (12) line-of-balance technique; (13) time management; (14) recapitulization; and (15) analysis.
Amirghasemi, Mehrdad; Zamani, Reza
2014-01-01
This paper presents an effective procedure for solving the job shop problem. Synergistically combining small and large neighborhood schemes, the procedure consists of four components, namely (i) a construction method for generating semi-active schedules by a forward-backward mechanism, (ii) a local search for manipulating a small neighborhood structure guided by a tabu list, (iii) a feedback-based mechanism for perturbing the solutions generated, and (iv) a very large-neighborhood local search guided by a forward-backward shifting bottleneck method. The combination of shifting bottleneck mechanism and tabu list is used as a means of the manipulation of neighborhood structures, and the perturbation mechanism employed diversifies the search. A feedback mechanism, called repeat-check, detects consequent repeats and ignites a perturbation when the total number of consecutive repeats for two identical makespan values reaches a given threshold. The results of extensive computational experiments on the benchmark instances indicate that the combination of these four components is synergetic, in the sense that they collectively make the procedure fast and robust. PMID:24808999
User requirements for a patient scheduling system
NASA Technical Reports Server (NTRS)
Zimmerman, W.
1979-01-01
A rehabilitation institute's needs and wants from a scheduling system were established by (1) studying the existing scheduling system and the variables that affect patient scheduling, (2) conducting a human-factors study to establish the human interfaces that affect patients' meeting prescribed therapy schedules, and (3) developing and administering a questionnaire to the staff which pertains to the various interface problems in order to identify staff requirements to minimize scheduling problems and other factors that may limit the effectiveness of any new scheduling system.
Tao, Liang; McCurdy, Bill; Rescigno, Tom
2010-06-10
Our previously developed finite-element/ discrete variable representation in prolate spheroidal coordinates is extended to two-electron systems with a study of double ionization of H$_2$ with fixed-nuclei. Particular attention is paid to the development of fast and accurate methods for treating the electron-electron interaction. The use of exterior complex scaling in the implementation offers a simple way of enforcing Coulomb boundary conditions for the electronic double continuum. While the angular distributions calculated in this study are found to be completely consistent with our earlier treatments that employed single-center expansions in spherical coordinates, we find that the magnitude of the integrated cross sections are sensitive to small changes in the initial-state wave function. The present formulation offers significant advantages with respect to convergence and efficiency and opens the way to calculations on more complicated diatomic targets.
ERIC Educational Resources Information Center
Iversen, Synnove; Knivsberg, Ann-Mari; Ellertsen, Bjorn; Nodland, Magne; Larsen, Tommy Bade
2006-01-01
Incidence, severity and types of motor difficulties in children with severe behavioural and emotional problems were evaluated. A group of 6-year-olds (n = 29) with such problems and controls (n = 29) were compared on the Movement Assessment Battery for Children (M-ABC). The groups were compared on total scores as well as manual dexterity, ball…
Coordinating Shared Activities
NASA Technical Reports Server (NTRS)
Clement, Bradley
2004-01-01
Shared Activity Coordination (ShAC) is a computer program for planning and scheduling the activities of an autonomous team of interacting spacecraft and exploratory robots. ShAC could also be adapted to such terrestrial uses as helping multiple factory managers work toward competing goals while sharing such common resources as floor space, raw materials, and transports. ShAC iteratively invokes the Continuous Activity Scheduling Planning Execution and Replanning (CASPER) program to replan and propagate changes to other planning programs in an effort to resolve conflicts. A domain-expert specifies which activities and parameters thereof are shared and reports the expected conditions and effects of these activities on the environment. By specifying these conditions and effects differently for each planning program, the domain-expert subprogram defines roles that each spacecraft plays in a coordinated activity. The domain-expert subprogram also specifies which planning program has scheduling control over each shared activity. ShAC enables sharing of information, consensus over the scheduling of collaborative activities, and distributed conflict resolution. As the other planning programs incorporate new goals and alter their schedules in the changing environment, ShAC continually coordinates to respond to unexpected events.
Scheduling with genetic algorithms
NASA Technical Reports Server (NTRS)
Fennel, Theron R.; Underbrink, A. J., Jr.; Williams, George P. W., Jr.
1994-01-01
In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.
Development of Watch Schedule Using Rules Approach
NASA Astrophysics Data System (ADS)
Jurkevicius, Darius; Vasilecas, Olegas
The software for schedule creation and optimization solves a difficult, important and practical problem. The proposed solution is an online employee portal where administrator users can create and manage watch schedules and employee requests. Each employee can login with his/her own account and see his/her assignments, manage requests, etc. Employees set as administrators can perform the employee scheduling online, manage requests, etc. This scheduling software allows users not only to see the initial and optimized watch schedule in a simple and understandable form, but also to create special rules and criteria and input their business. The system using rules automatically will generate watch schedule.
NASA Astrophysics Data System (ADS)
Li, Chen; Lu, Zhiqiang; Han, Xiaole; Zhang, Yuejun; Wang, Li
2016-03-01
The integrated scheduling of container handling systems aims to optimize the coordination and overall utilization of all handling equipment, so as to minimize the makespan of a given set of container tasks. A modified disjunctive graph is proposed and a mixed 0-1 programming model is formulated. A heuristic algorithm is presented, in which the original problem is divided into two subproblems. In the first subproblem, contiguous bay crane operations are applied to obtain a good quay crane schedule. In the second subproblem, proper internal truck and yard crane schedules are generated to match the given quay crane schedule. Furthermore, a genetic algorithm based on the heuristic algorithm is developed to search for better solutions. The computational results show that the proposed algorithm can efficiently find high-quality solutions. They also indicate the effectiveness of simultaneous loading and discharging operations compared with separate ones.
Intelligent perturbation algorithms for space scheduling optimization
NASA Technical Reports Server (NTRS)
Kurtzman, Clifford R.
1991-01-01
Intelligent perturbation algorithms for space scheduling optimization are presented in the form of the viewgraphs. The following subject areas are covered: optimization of planning, scheduling, and manifesting; searching a discrete configuration space; heuristic algorithms used for optimization; use of heuristic methods on a sample scheduling problem; intelligent perturbation algorithms are iterative refinement techniques; properties of a good iterative search operator; dispatching examples of intelligent perturbation algorithm and perturbation operator attributes; scheduling implementations using intelligent perturbation algorithms; major advances in scheduling capabilities; the prototype ISF (industrial Space Facility) experiment scheduler; optimized schedule (max revenue); multi-variable optimization; Space Station design reference mission scheduling; ISF-TDRSS command scheduling demonstration; and example task - communications check.
Scheduler Design Criteria: Requirements and Considerations
NASA Technical Reports Server (NTRS)
Lee, Hanbong
2016-01-01
This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.
Decomposability and scalability in space-based observatory scheduling
NASA Technical Reports Server (NTRS)
Muscettola, Nicola; Smith, Stephen F.
1992-01-01
In this paper, we discuss issues of problem and model decomposition within the HSTS scheduling framework. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) scheduling problem, motivated by the limitations of the current solution and, more generally, the insufficiency of classical planning and scheduling approaches in this problem context. We first summarize the salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research. Then, we describe some key problem decomposition techniques supported by HSTS and underlying our integrated planning and scheduling approach, and we discuss the leverage they provide in solving space-based observatory scheduling problems.
Scheduling for indoor visible light communication based on graph theory.
Tao, Yuyang; Liang, Xiao; Wang, Jiaheng; Zhao, Chunming
2015-02-01
Visible light communication (VLC) has drawn much attention in the field of high-rate indoor wireless communication. While most existing works focused on point-to-point VLC technologies, few studies have concerned multiuser VLC, where multiple optical access points (APs) transmit data to multiple user receivers. In such scenarios, inter-user interference constitutes the major factor limiting the system performance. Therefore, a proper scheduling scheme has to be proposed to coordinate the interference and optimize the whole system performance. In this work, we aim to maximize the sum rate of the system while taking into account user fairness by appropriately assigning LED lamps to multiple users. The formulated scheduling problem turns out to be a maximum weighted independent set problem. We then propose a novel and efficient resource allocation method based on graph theory to achieve high sum rates. Moreover, we also introduce proportional fairness into our scheduling scheme to ensure the user fairness. Our proposed scheduling scheme can, with low complexity, achieve more multiplexing gains, higher sum rate, and better fairness than the existing works. PMID:25836136
ASTER Scheduling Prioritization Function
NASA Technical Reports Server (NTRS)
Cohen, Ron
1996-01-01
ASTER schedules are generated by an automated scheduling system. This scheduler will generate psuedo-optimal schedules based on a priority scheme. This priority scheme is controlled by the Science Team.
Scheduling Software for Complex Scenarios
NASA Technical Reports Server (NTRS)
2006-01-01
Preparing a vehicle and its payload for a single launch is a complex process that involves thousands of operations. Because the equipment and facilities required to carry out these operations are extremely expensive and limited in number, optimal assignment and efficient use are critically important. Overlapping missions that compete for the same resources, ground rules, safety requirements, and the unique needs of processing vehicles and payloads destined for space impose numerous constraints that, when combined, require advanced scheduling. Traditional scheduling systems use simple algorithms and criteria when selecting activities and assigning resources and times to each activity. Schedules generated by these simple decision rules are, however, frequently far from optimal. To resolve mission-critical scheduling issues and predict possible problem areas, NASA historically relied upon expert human schedulers who used their judgment and experience to determine where things should happen, whether they will happen on time, and whether the requested resources are truly necessary.
41 CFR 101-5.104-4 - Scheduling feasibility studies.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 41 Public Contracts and Property Management 2 2013-07-01 2012-07-01 true Scheduling feasibility... FEDERAL BUILDINGS AND COMPLEXES 5.1-General § 101-5.104-4 Scheduling feasibility studies. The schedule of feasibility studies will be coordinated by GSA with its construction, space management, and...
41 CFR 101-5.104-4 - Scheduling feasibility studies.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 41 Public Contracts and Property Management 2 2014-07-01 2012-07-01 true Scheduling feasibility... FEDERAL BUILDINGS AND COMPLEXES 5.1-General § 101-5.104-4 Scheduling feasibility studies. The schedule of feasibility studies will be coordinated by GSA with its construction, space management, and...
41 CFR 101-5.104-4 - Scheduling feasibility studies.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 41 Public Contracts and Property Management 2 2012-07-01 2012-07-01 false Scheduling feasibility... FEDERAL BUILDINGS AND COMPLEXES 5.1-General § 101-5.104-4 Scheduling feasibility studies. The schedule of feasibility studies will be coordinated by GSA with its construction, space management, and...
Satellite mission scheduling algorithm based on GA
NASA Astrophysics Data System (ADS)
Sun, Baolin; Mao, Lifei; Wang, Wenxiang; Xie, Xing; Qin, Qianqing
2007-11-01
The Satellite Mission Scheduling problem (SMS) involves scheduling tasks to be performed by a satellite, where new task requests can arrive at any time, non-deterministically, and must be scheduled in real-time. This paper describes a new Satellite Mission Scheduling problem based on Genetic Algorithm (SMSGA). In this paper, it investigates algorithmic approaches for determining an optimal or near-optimal sequence of tasks, allocated to a satellite payload over time, with dynamic tasking considerations. The simulation results show that the proposed approach is effective and efficient in applications to the real problems.
NASA Astrophysics Data System (ADS)
Holota, Petr; Nesvadba, Otakar
2015-04-01
In this paper the reciprocal distance is used for generating Galerkin's approximations in the weak solution of Neumann's problem that has an important role in Earth's gravity field studies. The reciprocal distance has a natural tie to the fundamental solution of Laplace's partial differential equation and in the paper it is represented by means of an expansion into a series of oblate spheroidal harmonics. Subsequently, the gradient vector of the reciprocal distance is constructed. In the computation of its components the expansion mentioned above is employed. The paper then focuses on the scalar product of reciprocal distance gradients in two different points and in particular on a series representation of a volume integral of the scalar product spread over an unbounded domain given by the exterior of an oblate spheroid (oblate ellipsoid of revolution). The integral yields the entries of Galerkin's matrix. The numerical interpretation of all the expansions used as well as the respective software implementation within the OpenCL framework is treated, which concerns also a numerical evaluation of Legendre functions of a real and an imaginary argument. In parallel an approximate closed formula expressing the entries of Galerkin's matrix (with an accuracy up to terms multiplied by the square of numerical eccentricity) is derived for convenience and comparison. The paper is added extensive numerical examples that illustrate the approach applied and demonstrate the accuracy of the derived formulas. Aspects related to practical applications are discussed.
Gang scheduling a parallel machine
Gorda, B.C.; Brooks, E.D. III.
1991-03-01
Program development on parallel machines can be a nightmare of scheduling headaches. We have developed a portable time sharing mechanism to handle the problem of scheduling gangs of processors. User program and their gangs of processors are put to sleep and awakened by the gang scheduler to provide a time sharing environment. Time quantums are adjusted according to priority queues and a system of fair share accounting. The initial platform for this software is the 128 processor BBN TC2000 in use in the Massively Parallel Computing Initiative at the Lawrence Livermore National Laboratory. 2 refs., 1 fig.