Improved personalized recommendation based on a similarity network

NASA Astrophysics Data System (ADS)

Wang, Ximeng; Liu, Yun; Xiong, Fei

2016-08-01

A recommender system helps individual users find the preferred items rapidly and has attracted extensive attention in recent years. Many successful recommendation algorithms are designed on bipartite networks, such as network-based inference or heat conduction. However, most of these algorithms define the resource-allocation methods for an average allocation. That is not reasonable because average allocation cannot indicate the user choice preference and the influence between users which leads to a series of non-personalized recommendation results. We propose a personalized recommendation approach that combines the similarity function and bipartite network to generate a similarity network that improves the resource-allocation process. Our model introduces user influence into the recommender system and states that the user influence can make the resource-allocation process more reasonable. We use four different metrics to evaluate our algorithms for three benchmark data sets. Experimental results show that the improved recommendation on a similarity network can obtain better accuracy and diversity than some competing approaches.

Resource Allocation in a Repetitive Project Scheduling Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Samuel, Biju; Mathew, Jeeno

2018-03-01

Resource Allocation is procedure of doling out or allocating the accessible assets in a monetary way and productive way. Resource allocation is the scheduling of the accessible assets and accessible exercises or activities required while thinking about both the asset accessibility and the total project completion time. Asset provisioning and allocation takes care of that issue by permitting the specialist co-ops to deal with the assets for every individual demand of asset. A probabilistic selection procedure has been developed in order to ensure various selections of chromosomes

Research of improved banker algorithm

NASA Astrophysics Data System (ADS)

Yuan, Xingde; Xu, Hong; Qiao, Shijiao

2013-03-01

In the multi-process operating system, resource management strategy of system is a critical global issue, especially when many processes implicating for the limited resources, since unreasonable scheduling will cause dead lock. The most classical solution for dead lock question is the banker algorithm; however, it has its own deficiency and only can avoid dead lock occurring in a certain extent. This article aims at reducing unnecessary safety checking, and then uses the new allocation strategy to improve the banker algorithm. Through full analysis and example verification of the new allocation strategy, the results show the improved banker algorithm obtains substantial increase in performance.

Time-aware service-classified spectrum defragmentation algorithm for flex-grid optical networks

NASA Astrophysics Data System (ADS)

Qiu, Yang; Xu, Jing

2018-01-01

By employing sophisticated routing and spectrum assignment (RSA) algorithms together with a finer spectrum granularity (namely frequency slot) in resource allocation procedures, flex-grid optical networks can accommodate diverse kinds of services with high spectrum-allocation flexibility and resource-utilization efficiency. However, the continuity and the contiguity constraints in spectrum allocation procedures may always induce some isolated, small-sized, and unoccupied spectral blocks (known as spectrum fragments) in flex-grid optical networks. Although these spectrum fragments are left unoccupied, they can hardly be utilized by the subsequent service requests directly because of their spectral characteristics and the constraints in spectrum allocation. In this way, the existence of spectrum fragments may exhaust the available spectrum resources for a coming service request and thus worsens the networking performance. Therefore, many reactive defragmentation algorithms have been proposed to handle the fragmented spectrum resources via re-optimizing the routing paths and the spectrum resources for the existing services. But the routing-path and the spectrum-resource re-optimization in reactive defragmentation algorithms may possibly disrupt the traffic of the existing services and require extra components. By comparison, some proactive defragmentation algorithms (e.g. fragmentation-aware algorithms) were proposed to suppress spectrum fragments from their generation instead of handling the fragmented spectrum resources. Although these proactive defragmentation algorithms induced no traffic disruption and required no extra components, they always left the generated spectrum fragments unhandled, which greatly affected their efficiency in spectrum defragmentation. In this paper, by comprehensively considering the characteristics of both the reactive and the proactive defragmentation algorithms, we proposed a time-aware service-classified (TASC) spectrum defragmentation algorithm, which simultaneously employed proactive and reactive mechanisms in suppressing spectrum fragments with the awareness of services' types and their duration times. By dividing the spectrum resources into several flexible groups according to services' types and limiting both the spectrum allocation and the spectrum re-tuning for a certain service inside one specific spectrum group according to its type, the proposed TASC defragmentation algorithm cannot only suppress spectrum fragments from generation inside each spectrum group, but also handle the fragments generated between two adjacent groups. In this way, the proposed TASC algorithm gains higher efficiency in suppressing spectrum fragments than both the reactive and the proactive defragmentation algorithms. Additionally, as the generation of spectrum fragments is retrained between spectrum groups and the defragmentation procedure is limited inside each spectrum group, the induced traffic disruption for the existing services can be possibly reduced. Besides, the proposed TASC defragmentation algorithm always re-tunes the spectrum resources of the service with the maximum duration time first in spectrum defragmentation procedure, which can further reduce spectrum fragments because of the fact that the services with longer duration times always have higher possibility in inducing spectrum fragments than the services with shorter duration times. The simulation results show that the proposed TASC defragmentation algorithm can significantly reduce the number of the generated spectrum fragments while improving the service blocking performance.

Fuzzy-logic based Q-Learning interference management algorithms in two-tier networks

NASA Astrophysics Data System (ADS)

Xu, Qiang; Xu, Zezhong; Li, Li; Zheng, Yan

2017-10-01

Unloading from macrocell network and enhancing coverage can be realized by deploying femtocells in the indoor scenario. However, the system performance of the two-tier network could be impaired by the co-tier and cross-tier interference. In this paper, a distributed resource allocation scheme is studied when each femtocell base station is self-governed and the resource cannot be assigned centrally through the gateway. A novel Q-Learning interference management scheme is proposed, that is divided into cooperative and independent part. In the cooperative algorithm, the interference information is exchanged between the cell-edge users which are classified by the fuzzy logic in the same cell. Meanwhile, we allocate the orthogonal subchannels to the high-rate cell-edge users to disperse the interference power when the data rate requirement is satisfied. The resource is assigned directly according to the minimum power principle in the independent algorithm. Simulation results are provided to demonstrate the significant performance improvements in terms of the average data rate, interference power and energy efficiency over the cutting-edge resource allocation algorithms.

Research on strategy and optimization method of PRT empty vehicles resource allocation based on traffic demand forecast

NASA Astrophysics Data System (ADS)

Xiang, Yu; Tao, Cheng

2018-05-01

During the operation of the personal rapid transit system(PRT), the empty vehicle resources is distributed unevenly because of different passenger demand. In order to maintain the balance between supply and demand, and to meet the passenger needs of the ride, PRT empty vehicle resource allocation model is constructed based on the future demand forecasted by historical demand in this paper. The improved genetic algorithm is implied in distribution of the empty vehicle which can reduce the customers waiting time and improve the operation efficiency of the PRT system so that all passengers can take the PRT vehicles in the shortest time. The experimental result shows that the improved genetic algorithm can allocate the empty vehicle from the system level optimally, and realize the distribution of the empty vehicle resources reasonably in the system.

Multi-Agent Coordination Techniques for Naval Tactical Combat Resources Management

DTIC Science & Technology

2008-07-01

resource coordination and cooperation problems. The combat resource allocation planning problem is treated in the companion report [2]. 2.3 Resource...report focuses on the resource coordination problem, while allocation algorithms are discussed in the companion report [2]. First, coordination in...classification of each should be indicated as with the title.) Canada’s Leader in Defence and National Security Science and Technology Chef de file au Canada en

Mass and Volume Optimization of Space Flight Medical Kits

NASA Technical Reports Server (NTRS)

Keenan, A. B.; Foy, Millennia Hope; Myers, Jerry

2014-01-01

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Assessing system reliability and allocating resources: a bayesian approach that integrates multi-level data

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

Graves, Todd L; Hamada, Michael S

2008-01-01

Good estimates of the reliability of a system make use of test data and expert knowledge at all available levels. Furthermore, by integrating all these information sources, one can determine how best to allocate scarce testing resources to reduce uncertainty. Both of these goals are facilitated by modern Bayesian computational methods. We apply these tools to examples that were previously solvable only through the use of ingenious approximations, and use genetic algorithms to guide resource allocation.

Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim

NASA Astrophysics Data System (ADS)

Aneri, Parikh; Sumathy, S.

2017-11-01

Cloud computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the Cloud Computing is consumer provider model. Cloud provider provides resources which consumer can access using cloud computing model in order to build their application based on their demand. Cloud data center is a bulk of resources on shared pool architecture for cloud user to access. Virtualization is the heart of the Cloud computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this cloud computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase cloud resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. CloudSim used in this proposal is an extensible toolkit and it simulates cloud computing environment.

Cooperative network clustering and task allocation for heterogeneous small satellite network

NASA Astrophysics Data System (ADS)

Qin, Jing

The research of small satellite has emerged as a hot topic in recent years because of its economical prospects and convenience in launching and design. Due to the size and energy constraints of small satellites, forming a small satellite network(SSN) in which all the satellites cooperate with each other to finish tasks is an efficient and effective way to utilize them. In this dissertation, I designed and evaluated a weight based dominating set clustering algorithm, which efficiently organizes the satellites into stable clusters. The traditional clustering algorithms of large monolithic satellite networks, such as formation flying and satellite swarm, are often limited on automatic formation of clusters. Therefore, a novel Distributed Weight based Dominating Set(DWDS) clustering algorithm is designed to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. A minimum dominating set is chosen as the candidate cluster head set based on their weights, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds. The Deadline Based Resource Balancing (DBRB) task allocation algorithm is designed for efficient task allocations in heterogeneous LEO small satellite networks. In the task allocation process, the dispatcher needs to consider the deadlines of the tasks as well as the residue energy of different resources for best energy utilization. We assume the tasks adopt a Map-Reduce framework, in which a task can consist of multiple subtasks. The DBRB algorithm is deployed on the head node of a cluster. It gathers the status from each cluster member and calculates their Node Importance Factors (NIFs) from the carried resources, residue power and compute capacity. The algorithm calculates the number of concurrent subtasks based on the deadlines, and allocates the subtasks to the nodes according to their NIF values. The simulation results show that when cluster members carry multiple resources, resource are more balanced and rare resources serve longer in DBRB than in the Earliest Deadline First algorithm. We also show that the algorithm performs well in service isolation by serving multiple tasks with different deadlines. Moreover, the average task response time with various cluster size settings is well controlled within deadlines as well. Except non-realtime tasks, small satellites may execute realtime tasks as well. The location-dependent tasks, such as image capturing, data transmission and remote sensing tasks are realtime tasks that are required to be started / finished on specific time. The resource energy balancing algorithm for realtime and non-realtime mixed workload is developed to efficiently schedule the tasks for best system performance. It calculates the residue energy for each resource type and tries to preserve resources and node availability when distributing tasks. Non-realtime tasks can be preempted by realtime tasks to provide better QoS to realtime tasks. I compared the performance of proposed algorithm with a random-priority scheduling algorithm, with only realtime tasks, non-realtime tasks and mixed tasks. It shows the resource energy reservation algorithm outperforms the latter one with both balanced and imbalanced workloads. Although the resource energy balancing task allocation algorithm for mixed workload provides preemption mechanism for realtime tasks, realtime tasks can still fail due to resource exhaustion. For LEO small satellite flies around the earth on stable orbits, the location-dependent realtime tasks can be considered as periodical tasks. Therefore, it is possible to reserve energy for these realtime tasks. The resource energy reservation algorithm preserves energy for the realtime tasks when the execution routine of periodical realtime tasks is known. In order to reserve energy for tasks starting very early in each period that the node does not have enough energy charged, an energy wrapping mechanism is also designed to calculate the residue energy from the previous period. The simulation results show that without energy reservation, realtime task failure rate can reach more than 60% when the workload is highly imbalanced. In contrast, the resource energy reservation produces zero RT task failures and leads to equal or better aggregate system throughput than the non-reservation algorithm. The proposed algorithm also preserves more energy because it avoids task preemption. (Abstract shortened by ProQuest.).

Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

2016-02-01

With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

Applications of artificial intelligence to mission planning

NASA Technical Reports Server (NTRS)

Ford, Donnie R.; Floyd, Stephen A.; Rogers, John S.

1990-01-01

The following subject areas are covered: object-oriented programming task; rule-based programming task; algorithms for resource allocation; connecting a Symbolics to a VAX; FORTRAN from Lisp; trees and forest task; software data structure conversion; software functionality modifications and enhancements; portability of resource allocation to a TI MicroExplorer; frontier of feasibility software system; and conclusions.

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Comparison of OPC job prioritization schemes to generate data for mask manufacturing

NASA Astrophysics Data System (ADS)

Lewis, Travis; Veeraraghavan, Vijay; Jantzen, Kenneth; Kim, Stephen; Park, Minyoung; Russell, Gordon; Simmons, Mark

2015-03-01

Delivering mask ready OPC corrected data to the mask shop on-time is critical for a foundry to meet the cycle time commitment for a new product. With current OPC compute resource sharing technology, different job scheduling algorithms are possible, such as, priority based resource allocation and fair share resource allocation. In order to maximize computer cluster efficiency, minimize the cost of the data processing and deliver data on schedule, the trade-offs of each scheduling algorithm need to be understood. Using actual production jobs, each of the scheduling algorithms will be tested in a production tape-out environment. Each scheduling algorithm will be judged on its ability to deliver data on schedule and the trade-offs associated with each method will be analyzed. It is now possible to introduce advance scheduling algorithms to the OPC data processing environment to meet the goals of on-time delivery of mask ready OPC data while maximizing efficiency and reducing cost.

A Subcarrier-Pair Based Resource Allocation Scheme Using Proportional Fairness for Cooperative OFDM-Based Cognitive Radio Networks

PubMed Central

Ma, Yongtao; Zhou, Liuji; Liu, Kaihua

2013-01-01

The paper presents a joint subcarrier-pair based resource allocation algorithm in order to improve the efficiency and fairness of cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. A communication model where one source node communicates with one destination node assisted by one half-duplex decode-and-forward (DF) relay is considered in the paper. An interference-limited environment is considered, with the constraint of transmitted sum-power over all channels and aggregate average interference towards multiple primary users (PUs). The proposed resource allocation algorithm is capable of maximizing both the system transmission efficiency and fairness among secondary users (SUs). Besides, the proposed algorithm can also keep the interference introduced to the PU bands below a threshold. A proportional fairness constraint is used to assure that each SU can achieve a required data rate, with quality of service guarantees. Moreover, we extend the analysis to the scenario where each cooperative SU has no channel state information (CSI) about non-adjacent links. We analyzed the throughput and fairness tradeoff in CR system. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results. PMID:23939586

Real time target allocation in cooperative unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kudleppanavar, Ganesh

The prolific development of Unmanned Aerial Vehicles (UAV's) in recent years has the potential to provide tremendous advantages in military, commercial and law enforcement applications. While safety and performance take precedence in the development lifecycle, autonomous operations and, in particular, cooperative missions have the ability to significantly enhance the usability of these vehicles. The success of cooperative missions relies on the optimal allocation of targets while taking into consideration the resource limitation of each vehicle. The task allocation process can be centralized or decentralized. This effort presents the development of a real time target allocation algorithm that considers available stored energy in each vehicle while minimizing the communication between each UAV. The algorithm utilizes a nearest neighbor search algorithm to locate new targets with respect to existing targets. Simulations show that this novel algorithm compares favorably to the mixed integer linear programming method, which is computationally more expensive. The implementation of this algorithm on Arduino and Xbee wireless modules shows the capability of the algorithm to execute efficiently on hardware with minimum computation complexity.

Dynamic optical resource allocation for mobile core networks with software defined elastic optical networking.

PubMed

Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo

2016-07-25

Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.

The Method for Assigning Priority Levels (MAPLe): A new decision-support system for allocating home care resources

PubMed Central

Hirdes, John P; Poss, Jeff W; Curtin-Telegdi, Nancy

2008-01-01

Background Home care plays a vital role in many health care systems, but there is evidence that appropriate targeting strategies must be used to allocate limited home care resources effectively. The aim of the present study was to develop and validate a methodology for prioritizing access to community and facility-based services for home care clients. Methods Canadian and international data based on the Resident Assessment Instrument – Home Care (RAI-HC) were analyzed to identify predictors for nursing home placement, caregiver distress and for being rated as requiring alternative placement to improve outlook. Results The Method for Assigning Priority Levels (MAPLe) algorithm was a strong predictor of all three outcomes in the derivation sample. The algorithm was validated with additional data from five other countries, three other provinces, and an Ontario sample obtained after the use of the RAI-HC was mandated. Conclusion The MAPLe algorithm provides a psychometrically sound decision-support tool that may be used to inform choices related to allocation of home care resources and prioritization of clients needing community or facility-based services. PMID:18366782

Resource Balancing Control Allocation

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Bodson, Marc

2010-01-01

Next generation aircraft with a large number of actuators will require advanced control allocation methods to compute the actuator commands needed to follow desired trajectories while respecting system constraints. Previously, algorithms were proposed to minimize the l1 or l2 norms of the tracking error and of the control effort. The paper discusses the alternative choice of using the l1 norm for minimization of the tracking error and a normalized l(infinity) norm, or sup norm, for minimization of the control effort. The algorithm computes the norm of the actuator deflections scaled by the actuator limits. Minimization of the control effort then translates into the minimization of the maximum actuator deflection as a percentage of its range of motion. The paper shows how the problem can be solved effectively by converting it into a linear program and solving it using a simplex algorithm. Properties of the algorithm are investigated through examples. In particular, the min-max criterion results in a type of resource balancing, where the resources are the control surfaces and the algorithm balances these resources to achieve the desired command. A study of the sensitivity of the algorithms to the data is presented, which shows that the normalized l(infinity) algorithm has the lowest sensitivity, although high sensitivities are observed whenever the limits of performance are reached.

Algorithms for synthesizing management solutions based on OLAP-technologies

NASA Astrophysics Data System (ADS)

Pishchukhin, A. M.; Akhmedyanova, G. F.

2018-05-01

OLAP technologies are a convenient means of analyzing large amounts of information. An attempt was made in their work to improve the synthesis of optimal management decisions. The developed algorithms allow forecasting the needs and accepted management decisions on the main types of the enterprise resources. Their advantage is the efficiency, based on the simplicity of quadratic functions and differential equations of only the first order. At the same time, the optimal redistribution of resources between different types of products from the assortment of the enterprise is carried out, and the optimal allocation of allocated resources in time. The proposed solutions can be placed on additional specially entered coordinates of the hypercube representing the data warehouse.

Optimizing Medical Kits for Spaceflight

NASA Technical Reports Server (NTRS)

Keenan, A. B,; Foy, Millennia; Myers, G.

2014-01-01

The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.

An integrated model of water resources optimization allocation based on projection pursuit model - Grey wolf optimization method in a transboundary river basin

NASA Astrophysics Data System (ADS)

Yu, Sen; Lu, Hongwei

2018-04-01

Under the effects of global change, water crisis ranks as the top global risk in the future decade, and water conflict in transboundary river basins as well as the geostrategic competition led by it is most concerned. This study presents an innovative integrated PPMGWO model of water resources optimization allocation in a transboundary river basin, which is integrated through the projection pursuit model (PPM) and Grey wolf optimization (GWO) method. This study uses the Songhua River basin and 25 control units as examples, adopting the PPMGWO model proposed in this study to allocate the water quantity. Using water consumption in all control units in the Songhua River basin in 2015 as reference to compare with optimization allocation results of firefly algorithm (FA) and Particle Swarm Optimization (PSO) algorithms as well as the PPMGWO model, results indicate that the average difference between corresponding allocation results and reference values are 0.195 bil m3, 0.151 bil m3, and 0.085 bil m3, respectively. Obviously, the average difference of the PPMGWO model is the lowest and its optimization allocation result is closer to reality, which further confirms the reasonability, feasibility, and accuracy of the PPMGWO model. And then the PPMGWO model is adopted to simulate allocation of available water quantity in Songhua River basin in 2018, 2020, and 2030. The simulation results show water quantity which could be allocated in all controls demonstrates an overall increasing trend with reasonable and equal exploitation and utilization of water resources in the Songhua River basin in future. In addition, this study has a certain reference value and application meaning to comprehensive management and water resources allocation in other transboundary river basins.

Radio Resource Allocation on Complex 4G Wireless Cellular Networks

NASA Astrophysics Data System (ADS)

Psannis, Kostas E.

2015-09-01

In this article we consider the heuristic algorithm which improves step by step wireless data delivery over LTE cellular networks by using the total transmit power with the constraint on users’ data rates, and the total throughput with the constraints on the total transmit power as well as users’ data rates, which are jointly integrated into a hybrid-layer design framework to perform radio resource allocation for multiple users, and to effectively decide the optimal system parameter such as modulation and coding scheme (MCS) in order to adapt to the varying channel quality. We propose new heuristic algorithm which balances the accessible data rate, the initial data rates of each user allocated by LTE scheduler, the priority indicator which signals delay- throughput- packet loss awareness of the user, and the buffer fullness by achieving maximization of radio resource allocation for multiple users. It is noted that the overall performance is improved with the increase in the number of users, due to multiuser diversity. Experimental results illustrate and validate the accuracy of the proposed methodology.

Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

NASA Astrophysics Data System (ADS)

Shaat, Musbah; Bader, Faouzi

2010-12-01

Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

PubMed

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

Space Network Control Conference on Resource Allocation Concepts and Approaches

NASA Technical Reports Server (NTRS)

Moe, Karen L. (Editor)

1991-01-01

The results are presented of the Space Network Control (SNC) Conference. In the late 1990s, when the Advanced Tracking and Data Relay Satellite System is operational, Space Network communication services will be supported and controlled by the SNC. The goals of the conference were to survey existing resource allocation concepts and approaches, to identify solutions applicable to the Space Network, and to identify avenues of study in support of the SNC development. The conference was divided into three sessions: (1) Concepts for Space Network Allocation; (2) SNC and User Payload Operations Control Center (POCC) Human-Computer Interface Concepts; and (3) Resource Allocation Tools, Technology, and Algorithms. Key recommendations addressed approaches to achieving higher levels of automation in the scheduling process.

Dynamic Transfers Of Tasks Among Computers

NASA Technical Reports Server (NTRS)

Liu, Howard T.; Silvester, John A.

1989-01-01

Allocation scheme gives jobs to idle computers. Ideal resource-sharing algorithm should have following characteristics: Dynamics, decentralized, and heterogeneous. Proposed enhanced receiver-initiated dynamic algorithm (ERIDA) for resource sharing fulfills all above criteria. Provides method balancing workload among hosts, resulting in improvement in response time and throughput performance of total system. Adjusts dynamically to traffic load of each station.

Visual Perception Based Rate Control Algorithm for HEVC

NASA Astrophysics Data System (ADS)

Feng, Zeqi; Liu, PengYu; Jia, Kebin

2018-01-01

For HEVC, rate control is an indispensably important video coding technology to alleviate the contradiction between video quality and the limited encoding resources during video communication. However, the rate control benchmark algorithm of HEVC ignores subjective visual perception. For key focus regions, bit allocation of LCU is not ideal and subjective quality is unsatisfied. In this paper, a visual perception based rate control algorithm for HEVC is proposed. First bit allocation weight of LCU level is optimized based on the visual perception of luminance and motion to ameliorate video subjective quality. Then λ and QP are adjusted in combination with the bit allocation weight to improve rate distortion performance. Experimental results show that the proposed algorithm reduces average 0.5% BD-BR and maximum 1.09% BD-BR at no cost in bitrate accuracy compared with HEVC (HM15.0). The proposed algorithm devotes to improving video subjective quality under various video applications.

Motion-related resource allocation in dynamic wireless visual sensor network environments.

PubMed

Katsenou, Angeliki V; Kondi, Lisimachos P; Parsopoulos, Konstantinos E

2014-01-01

This paper investigates quality-driven cross-layer optimization for resource allocation in direct sequence code division multiple access wireless visual sensor networks. We consider a single-hop network topology, where each sensor transmits directly to a centralized control unit (CCU) that manages the available network resources. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each node, under four different quality-driven criteria that take into consideration the varying motion characteristics of each recorded video. For this purpose, we studied two approaches with a different tradeoff of quality and complexity. The first one allocates the resources individually for each sensor, whereas the second clusters them according to the recorded level of motion. In order to address the dynamic nature of the recorded scenery and re-allocate the resources whenever it is dictated by the changes in the amount of motion in the scenery, we propose a mechanism based on the particle swarm optimization algorithm, combined with two restarting schemes that either exploit the previously determined resource allocation or conduct a rough estimation of it. Experimental simulations demonstrate the efficiency of the proposed approaches.

Graph theoretical stable allocation as a tool for reproduction of control by human operators

NASA Astrophysics Data System (ADS)

van Nooijen, Ronald; Ertsen, Maurits; Kolechkina, Alla

2016-04-01

During the design of central control algorithms for existing water resource systems under manual control it is important to consider the interaction with parts of the system that remain under manual control and to compare the proposed new system with the existing manual methods. In graph theory the "stable allocation" problem has good solution algorithms and allows for formulation of flow distribution problems in terms of priorities. As a test case for the use of this approach we used the algorithm to derive water allocation rules for the Gezira Scheme, an irrigation system located between the Blue and White Niles south of Khartoum. In 1925, Gezira started with 300,000 acres; currently it covers close to two million acres.

Optimization-based Approach to Cross-layer Resource Management in Wireless Networked Control Systems

DTIC Science & Technology

2013-05-01

interest from both academia and industry [37], finding applications in un- manned robotic vehicles, automated highways and factories, smart homes and...is stable when the scaler varies slowly. The algorithm is further extended to utilize the slack resource in the network, which leads to the...model . . . . . . . . . . . . . . . . 66 Optimal sampling rate allocation formulation . . . . . 67 Price-based algorithm

SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres

NASA Astrophysics Data System (ADS)

Bi, Jing; Yuan, Haitao; Tie, Ming; Tan, Wei

2015-10-01

Dynamic virtualised resource allocation is the key to quality of service assurance for multi-tier web application services in cloud data centre. In this paper, we develop a self-management architecture of cloud data centres with virtualisation mechanism for multi-tier web application services. Based on this architecture, we establish a flexible hybrid queueing model to determine the amount of virtual machines for each tier of virtualised application service environments. Besides, we propose a non-linear constrained optimisation problem with restrictions defined in service level agreement. Furthermore, we develop a heuristic mixed optimisation algorithm to maximise the profit of cloud infrastructure providers, and to meet performance requirements from different clients as well. Finally, we compare the effectiveness of our dynamic allocation strategy with two other allocation strategies. The simulation results show that the proposed resource allocation method is efficient in improving the overall performance and reducing the resource energy cost.

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

NASA Astrophysics Data System (ADS)

Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni

2012-09-01

Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

Nash Social Welfare in Multiagent Resource Allocation

NASA Astrophysics Data System (ADS)

Ramezani, Sara; Endriss, Ulle

We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness considerations. We show that the problem of finding an optimal outcome is NP-hard for a number of different languages for representing agent preferences; we establish new results regarding convergence to Nash-optimal outcomes in a distributed negotiation framework; and we design and test algorithms similar to those applied in combinatorial auctions for computing such an outcome directly.

Distributed Bees Algorithm Parameters Optimization for a Cost Efficient Target Allocation in Swarms of Robots

PubMed Central

Jevtić, Aleksandar; Gutiérrez, Álvaro

2011-01-01

Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677

Computing the Envelope for Stepwise Constant Resource Allocations

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Clancy, Daniel (Technical Monitor)

2001-01-01

Estimating tight resource level is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with noises equal to the events and edges equal to the necessary predecessor links between events. The incremental solution of a staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. The staged algorithm has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible for use in the inner loop of search-based scheduling algorithms.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions.

PubMed

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-12-24

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions

PubMed Central

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-01-01

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources. PMID:28029118

Exploiting geo-distributed clouds for a e-health monitoring system with minimum service delay and privacy preservation.

PubMed

Shen, Qinghua; Liang, Xiaohui; Shen, Xuemin; Lin, Xiaodong; Luo, Henry Y

2014-03-01

In this paper, we propose an e-health monitoring system with minimum service delay and privacy preservation by exploiting geo-distributed clouds. In the system, the resource allocation scheme enables the distributed cloud servers to cooperatively assign the servers to the requested users under the load balance condition. Thus, the service delay for users is minimized. In addition, a traffic-shaping algorithm is proposed. The traffic-shaping algorithm converts the user health data traffic to the nonhealth data traffic such that the capability of traffic analysis attacks is largely reduced. Through the numerical analysis, we show the efficiency of the proposed traffic-shaping algorithm in terms of service delay and privacy preservation. Furthermore, through the simulations, we demonstrate that the proposed resource allocation scheme significantly reduces the service delay compared to two other alternatives using jointly the short queue and distributed control law.

Multiresource allocation and scheduling for periodic soft real-time applications

NASA Astrophysics Data System (ADS)

Gopalan, Kartik; Chiueh, Tzi-cker

2001-12-01

Real-time applications that utilize multiple system resources, such as CPU, disks, and network links, require coordinated scheduling of these resources in order to meet their end-to-end performance requirements. Most state-of-the-art operating systems support independent resource allocation and deadline-driven scheduling but lack coordination among multiple heterogeneous resources. This paper describes the design and implementation of an Integrated Real-time Resource Scheduler (IRS) that performs coordinated allocation and scheduling of multiple heterogeneous resources on the same machine for periodic soft real-time application. The principal feature of IRS is a heuristic multi-resource allocation algorithm that reserves multiple resources for real-time applications in a manner that can maximize the number of applications admitted into the system in the long run. At run-time, a global scheduler dispatches the tasks of the soft real-time application to individual resource schedulers according to the precedence constraints between tasks. The individual resource schedulers, which could be any deadline based schedulers, can make scheduling decisions locally and yet collectively satisfy a real-time application's performance requirements. The tightness of overall timing guarantees is ultimately determined by the properties of individual resource schedulers. However, IRS maximizes overall system resource utilization efficiency by coordinating deadline assignment across multiple tasks in a soft real-time application.

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

NASA Astrophysics Data System (ADS)

Andreotti, Riccardo; Del Fiorentino, Paolo; Giannetti, Filippo; Lottici, Vincenzo

2016-12-01

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium.

A QoS Aware Resource Allocation Strategy for 3D A/V Streaming in OFDMA Based Wireless Systems

PubMed Central

Chung, Young-uk; Choi, Yong-Hoon; Park, Suwon; Lee, Hyukjoon

2014-01-01

Three-dimensional (3D) video is expected to be a “killer app” for OFDMA-based broadband wireless systems. The main limitation of 3D video streaming over a wireless system is the shortage of radio resources due to the large size of the 3D traffic. This paper presents a novel resource allocation strategy to address this problem. In the paper, the video-plus-depth 3D traffic type is considered. The proposed resource allocation strategy focuses on the relationship between 2D video and the depth map, handling them with different priorities. It is formulated as an optimization problem and is solved using a suboptimal heuristic algorithm. Numerical results show that the proposed scheme provides a better quality of service compared to conventional schemes. PMID:25250377

Computer software tool REALM for sustainable water allocation and management.

PubMed

Perera, B J C; James, B; Kularathna, M D U

2005-12-01

REALM (REsource ALlocation Model) is a generalised computer simulation package that models harvesting and bulk distribution of water resources within a water supply system. It is a modeling tool, which can be applied to develop specific water allocation models. Like other water resource simulation software tools, REALM uses mass-balance accounting at nodes, while the movement of water within carriers is subject to capacity constraints. It uses a fast network linear programming algorithm to optimise the water allocation within the network during each simulation time step, in accordance with user-defined operating rules. This paper describes the main features of REALM and provides potential users with an appreciation of its capabilities. In particular, it describes two case studies covering major urban and rural water supply systems. These case studies illustrate REALM's capabilities in the use of stochastically generated data in water supply planning and management, modelling of environmental flows, and assessing security of supply issues.

An approximate dynamic programming approach to resource management in multi-cloud scenarios

NASA Astrophysics Data System (ADS)

Pietrabissa, Antonio; Priscoli, Francesco Delli; Di Giorgio, Alessandro; Giuseppi, Alessandro; Panfili, Martina; Suraci, Vincenzo

2017-03-01

The programmability and the virtualisation of network resources are crucial to deploy scalable Information and Communications Technology (ICT) services. The increasing demand of cloud services, mainly devoted to the storage and computing, requires a new functional element, the Cloud Management Broker (CMB), aimed at managing multiple cloud resources to meet the customers' requirements and, simultaneously, to optimise their usage. This paper proposes a multi-cloud resource allocation algorithm that manages the resource requests with the aim of maximising the CMB revenue over time. The algorithm is based on Markov decision process modelling and relies on reinforcement learning techniques to find online an approximate solution.

Computing the Envelope for Stepwise-Constant Resource Allocations

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Clancy, Daniel (Technical Monitor)

2002-01-01

Computing tight resource-level bounds is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with nodes equal to the events and edges equal to the necessary predecessor links between events. A staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. Each stage has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible and promising for use in the inner loop of flexible-time scheduling algorithms.

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Chaotic genetic algorithm and Adaboost ensemble metamodeling approach for optimum resource planning in emergency departments.

PubMed

Yousefi, Milad; Yousefi, Moslem; Ferreira, Ricardo Poley Martins; Kim, Joong Hoon; Fogliatto, Flavio S

2018-01-01

Long length of stay and overcrowding in emergency departments (EDs) are two common problems in the healthcare industry. To decrease the average length of stay (ALOS) and tackle overcrowding, numerous resources, including the number of doctors, nurses and receptionists need to be adjusted, while a number of constraints are to be considered at the same time. In this study, an efficient method based on agent-based simulation, machine learning and the genetic algorithm (GA) is presented to determine optimum resource allocation in emergency departments. GA can effectively explore the entire domain of all 19 variables and identify the optimum resource allocation through evolution and mimicking the survival of the fittest concept. A chaotic mutation operator is used in this study to boost GA performance. A model of the system needs to be run several thousand times through the GA evolution process to evaluate each solution, hence the process is computationally expensive. To overcome this drawback, a robust metamodel is initially constructed based on an agent-based system simulation. The simulation exhibits ED performance with various resource allocations and trains the metamodel. The metamodel is created with an ensemble of the adaptive neuro-fuzzy inference system (ANFIS), feedforward neural network (FFNN) and recurrent neural network (RNN) using the adaptive boosting (AdaBoost) ensemble algorithm. The proposed GA-based optimization approach is tested in a public ED, and it is shown to decrease the ALOS in this ED case study by 14%. Additionally, the proposed metamodel shows a 26.6% improvement compared to the average results of ANFIS, FFNN and RNN in terms of mean absolute percentage error (MAPE). Copyright © 2017 Elsevier B.V. All rights reserved.

Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

PubMed Central

Zhang, Guang-Qian; Wang, Jian-Jun; Liu, Ya-Jing

2014-01-01

m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem. PMID:24982933

Multimedia transmission in MC-CDMA using adaptive subcarrier power allocation and CFO compensation

NASA Astrophysics Data System (ADS)

Chitra, S.; Kumaratharan, N.

2018-02-01

Multicarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions.

Efficient Resources Provisioning Based on Load Forecasting in Cloud

PubMed Central

Hu, Rongdong; Jiang, Jingfei; Liu, Guangming; Wang, Lixin

2014-01-01

Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application's actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements. PMID:24701160

Short-term storage allocation in a filmless hospital

NASA Astrophysics Data System (ADS)

Strickland, Nicola H.; Deshaies, Marc J.; Reynolds, R. Anthony; Turner, Jonathan E.; Allison, David J.

1997-05-01

Optimizing limited short term storage (STS) resources requires gradual, systematic changes, monitored and modified within an operational PACS environment. Optimization of the centralized storage requires a balance of exam numbers and types in STS to minimize lengthy retrievals from long term archive. Changes to STS parameters and work procedures were made while monitoring the effects on resource allocation by analyzing disk space temporally. Proportions of disk space allocated to each patient category on STS were measured to approach the desired proportions in a controlled manner. Key factors for STS management were: (1) sophisticated exam prefetching algorithms: HIS/RIS-triggered, body part-related and historically-selected, and (2) a 'storage onion' design allocating various exam categories to layers with differential deletion protection. Hospitals planning for STS space should consider the needs of radiology, wards, outpatient clinics and clinicoradiological conferences for new and historical exams; desired on-line time; and potential increase in image throughput and changing resources, such as an increase in short term storage disk space.

Software for Allocating Resources in the Deep Space Network

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester; Zendejas, Silvino; Baldwin, John

2003-01-01

TIGRAS 2.0 is a computer program designed to satisfy a need for improved means for analyzing the tracking demands of interplanetary space-flight missions upon the set of ground antenna resources of the Deep Space Network (DSN) and for allocating those resources. Written in Microsoft Visual C++, TIGRAS 2.0 provides a single rich graphical analysis environment for use by diverse DSN personnel, by connecting to various data sources (relational databases or files) based on the stages of the analyses being performed. Notable among the algorithms implemented by TIGRAS 2.0 are a DSN antenna-load-forecasting algorithm and a conflict-aware DSN schedule-generating algorithm. Computers running TIGRAS 2.0 can also be connected using SOAP/XML to a Web services server that provides analysis services via the World Wide Web. TIGRAS 2.0 supports multiple windows and multiple panes in each window for users to view and use information, all in the same environment, to eliminate repeated switching among various application programs and Web pages. TIGRAS 2.0 enables the use of multiple windows for various requirements, trajectory-based time intervals during which spacecraft are viewable, ground resources, forecasts, and schedules. Each window includes a time navigation pane, a selection pane, a graphical display pane, a list pane, and a statistics pane.

Real-time robot deliberation by compilation and monitoring of anytime algorithms

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo

1994-01-01

Anytime algorithms are algorithms whose quality of results improves gradually as computation time increases. Certainty, accuracy, and specificity are metrics useful in anytime algorighm construction. It is widely accepted that a successful robotic system must trade off between decision quality and the computational resources used to produce it. Anytime algorithms were designed to offer such a trade off. A model of compilation and monitoring mechanisms needed to build robots that can efficiently control their deliberation time is presented. This approach simplifies the design and implementation of complex intelligent robots, mechanizes the composition and monitoring processes, and provides independent real time robotic systems that automatically adjust resource allocation to yield optimum performance.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks

PubMed Central

Guo, Wenzhong; Xiong, Naixue; Chao, Han-Chieh; Hussain, Sajid; Chen, Guolong

2011-01-01

In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms. PMID:22163971

Physical and Cross-Layer Security Enhancement and Resource Allocation for Wireless Networks

ERIC Educational Resources Information Center

Bashar, Muhammad Shafi Al

2011-01-01

In this dissertation, we present novel physical (PHY) and cross-layer design guidelines and resource adaptation algorithms to improve the security and user experience in the future wireless networks. Physical and cross-layer wireless security measures can provide stronger overall security with high efficiency and can also provide better…

QoS-Oriented High Dynamic Resource Allocation in Vehicular Communication Networks

PubMed Central

2014-01-01

Vehicular ad hoc networks (VANETs) are emerging as new research area and attracting an increasing attention from both industry and research communities. In this context, a dynamic resource allocation policy that maximizes the use of available resources and meets the quality of service (QoS) requirement of constraining applications is proposed. It is a combination of a fair packet scheduling policy and a new adaptive QoS oriented call admission control (CAC) scheme based on the vehicle density variation. This scheme decides whether the connection request is to be admitted into the system, while providing fair access and guaranteeing the desired throughput. The proposed algorithm showed good performance in testing in real world environment. PMID:24616639

Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch.

PubMed

Li, Chaojie; Yu, Xinghuo; Huang, Tingwen; He, Xing; Chaojie Li; Xinghuo Yu; Tingwen Huang; Xing He; Li, Chaojie; Huang, Tingwen; He, Xing; Yu, Xinghuo

2018-06-01

The resource allocation problem is studied and reformulated by a distributed interior point method via a -logarithmic barrier. By the facilitation of the graph Laplacian, a fully distributed continuous-time multiagent system is developed for solving the problem. Specifically, to avoid high singularity of the -logarithmic barrier at boundary, an adaptive parameter switching strategy is introduced into this dynamical multiagent system. The convergence rate of the distributed algorithm is obtained. Moreover, a novel distributed primal-dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution. The dual decomposition technique is applied to transform the optimization problem into easily solvable resource allocation subproblems with local inequality constraints. The good performance of the new dynamical systems is, respectively, verified by a numerical example and the IEEE six-bus test system-based simulations.

A trust-based sensor allocation algorithm in cooperative space search problems

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

2011-06-01

Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

2012-08-01

In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

Development a heuristic method to locate and allocate the medical centers to minimize the earthquake relief operation time.

PubMed

Aghamohammadi, Hossein; Saadi Mesgari, Mohammad; Molaei, Damoon; Aghamohammadi, Hasan

2013-01-01

Location-allocation is a combinatorial optimization problem, and is defined as Non deterministic Polynomial Hard (NP) hard optimization. Therefore, solution of such a problem should be shifted from exact to heuristic or Meta heuristic due to the complexity of the problem. Locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster management so that developing a proper method will reduce the time of relief operation and will consequently decrease the number of fatalities. This paper presents the development of a heuristic method based on two nested genetic algorithms to optimize this location allocation problem by using the abilities of Geographic Information System (GIS). In the proposed method, outer genetic algorithm is applied to the location part of the problem and inner genetic algorithm is used to optimize the resource allocation. The final outcome of implemented method includes the spatial location of new required medical centers. The method also calculates that how many of the injuries at each demanding point should be taken to any of the existing and new medical centers as well. The results of proposed method showed high performance of designed structure to solve a capacitated location-allocation problem that may arise in a disaster situation when injured people has to be taken to medical centers in a reasonable time.

Conflict-Aware Scheduling Algorithm

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester

2006-01-01

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Application of a Dynamic Programming Algorithm for Weapon Target Assignment

DTIC Science & Technology

2016-02-01

25] A . Turan , “Techniques for the Allocation of Resources Under Uncertainty,” Middle Eastern Technical University, Ankara, Turkey, 2012. [26] K...UNCLASSIFIED UNCLASSIFIED Application of a Dynamic Programming Algorithm for Weapon Target Assignment Lloyd Hammond Weapons and...optimisation techniques to support the decision making process. This report documents the methodology used to identify, develop and assess a

Adaptive Subframe Partitioning and Efficient Packet Scheduling in OFDMA Cellular System with Fixed Decode-and-Forward Relays

NASA Astrophysics Data System (ADS)

Wang, Liping; Ji, Yusheng; Liu, Fuqiang

The integration of multihop relays with orthogonal frequency-division multiple access (OFDMA) cellular infrastructures can meet the growing demands for better coverage and higher throughput. Resource allocation in the OFDMA two-hop relay system is more complex than that in the conventional single-hop OFDMA system. With time division between transmissions from the base station (BS) and those from relay stations (RSs), fixed partitioning of the BS subframe and RS subframes can not adapt to various traffic demands. Moreover, single-hop scheduling algorithms can not be used directly in the two-hop system. Therefore, we propose a semi-distributed algorithm called ASP to adjust the length of every subframe adaptively, and suggest two ways to extend single-hop scheduling algorithms into multihop scenarios: link-based and end-to-end approaches. Simulation results indicate that the ASP algorithm increases system utilization and fairness. The max carrier-to-interference ratio (Max C/I) and proportional fairness (PF) scheduling algorithms extended using the end-to-end approach obtain higher throughput than those using the link-based approach, but at the expense of more overhead for information exchange between the BS and RSs. The resource allocation scheme using ASP and end-to-end PF scheduling achieves a tradeoff between system throughput maximization and fairness.

A novel LTE scheduling algorithm for green technology in smart grid.

PubMed

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application's priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively.

A Novel LTE Scheduling Algorithm for Green Technology in Smart Grid

PubMed Central

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin; Chayon, Muhammad Hasibur Rashid

2015-01-01

Smart grid (SG) application is being used nowadays to meet the demand of increasing power consumption. SG application is considered as a perfect solution for combining renewable energy resources and electrical grid by means of creating a bidirectional communication channel between the two systems. In this paper, three SG applications applicable to renewable energy system, namely, distribution automation (DA), distributed energy system-storage (DER) and electrical vehicle (EV), are investigated in order to study their suitability in Long Term Evolution (LTE) network. To compensate the weakness in the existing scheduling algorithms, a novel bandwidth estimation and allocation technique and a new scheduling algorithm are proposed. The technique allocates available network resources based on application’s priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. Finally, the simulation results demonstrate that the proposed mechanism achieves higher throughput, lower delay and lower packet loss rate for DA and DER as well as provide a degree of service for EV. In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively. PMID:25830703

Implementation of a Space Communications Cognitive Engine

NASA Technical Reports Server (NTRS)

Hackett, Timothy M.; Bilen, Sven G.; Ferreira, Paulo Victor R.; Wyglinski, Alexander M.; Reinhart, Richard C.

2017-01-01

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).

New algorithms for optimal reduction of technical risks

NASA Astrophysics Data System (ADS)

Todinov, M. T.

2013-06-01

The article features exact algorithms for reduction of technical risk by (1) optimal allocation of resources in the case where the total potential loss from several sources of risk is a sum of the potential losses from the individual sources; (2) optimal allocation of resources to achieve a maximum reduction of system failure; and (3) making an optimal choice among competing risky prospects. The article demonstrates that the number of activities in a risky prospect is a key consideration in selecting the risky prospect. As a result, the maximum expected profit criterion, widely used for making risk decisions, is fundamentally flawed, because it does not consider the impact of the number of risk-reward activities in the risky prospects. A popular view, that if a single risk-reward bet with positive expected profit is unacceptable then a sequence of such identical risk-reward bets is also unacceptable, has been analysed and proved incorrect.

Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

NASA Astrophysics Data System (ADS)

Zhao, Yongxu; Chen, Yueyun; Mai, Zhiyuan

2018-01-01

In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

Fundamental resource-allocating model in colleges and universities based on Immune Clone Algorithms

NASA Astrophysics Data System (ADS)

Ye, Mengdie

2017-05-01

In this thesis we will seek the combination of antibodies and antigens converted from the optimal course arrangement and make an analogy with Immune Clone Algorithms. According to the character of the Algorithms, we apply clone, clone gene and clone selection to arrange courses. Clone operator can combine evolutionary search and random search, global search and local search. By cloning and clone mutating candidate solutions, we can find the global optimal solution quickly.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System.

PubMed

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-11-16

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

PubMed Central

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-01-01

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range. PMID:27854342

Research on memory management in embedded systems

NASA Astrophysics Data System (ADS)

Huang, Xian-ying; Yang, Wu

2005-12-01

Memory is a scarce resource in embedded system due to cost and size. Thus, applications in embedded systems cannot use memory randomly, such as in desktop applications. However, data and code must be stored into memory for running. The purpose of this paper is to save memory in developing embedded applications and guarantee running under limited memory conditions. Embedded systems often have small memory and are required to run a long time. Thus, a purpose of this study is to construct an allocator that can allocate memory effectively and bear a long-time running situation, reduce memory fragmentation and memory exhaustion. Memory fragmentation and exhaustion are related to the algorithm memory allocated. Static memory allocation cannot produce fragmentation. In this paper it is attempted to find an effective allocation algorithm dynamically, which can reduce memory fragmentation. Data is the critical part that ensures an application can run regularly, which takes up a large amount of memory. The amount of data that can be stored in the same size of memory is relevant with the selected data structure. Skills for designing application data in mobile phone are explained and discussed also.

An improved approach of register allocation via graph coloring

NASA Astrophysics Data System (ADS)

Gao, Lei; Shi, Ce

2005-03-01

Register allocation is an important part of optimizing compiler. The algorithm of register allocation via graph coloring is implemented by Chaitin and his colleagues firstly and improved by Briggs and others. By abstracting register allocation to graph coloring, the allocation process is simplified. As the physical register number is limited, coloring of the interference graph can"t succeed for every node. The uncolored nodes must be spilled. There is an assumption that almost all the allocation method obeys: when a register is allocated to a variable v, it can"t be used by others before v quit even if v is not used for a long time. This may causes a waste of register resource. The authors relax this restriction under certain conditions and make some improvement. In this method, one register can be mapped to two or more interfered "living" live ranges at the same time if they satisfy some requirements. An operation named merge is defined which can arrange two interfered nodes occupy the same register with some cost. Thus, the resource of register can be used more effectively and the cost of memory access can be reduced greatly.

Multi-layer service function chaining scheduling based on auxiliary graph in IP over optical network

NASA Astrophysics Data System (ADS)

Li, Yixuan; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Software Defined Optical Network (SDON) can be considered as extension of Software Defined Network (SDN) in optical networks. SDON offers a unified control plane and makes optical network an intelligent transport network with dynamic flexibility and service adaptability. For this reason, a comprehensive optical transmission service, able to achieve service differentiation all the way down to the optical transport layer, can be provided to service function chaining (SFC). IP over optical network, as a promising networking architecture to interconnect data centers, is the most widely used scenarios of SFC. In this paper, we offer a flexible and dynamic resource allocation method for diverse SFC service requests in the IP over optical network. To do so, we firstly propose the concept of optical service function (OSF) and a multi-layer SFC model. OSF represents the comprehensive optical transmission service (e.g., multicast, low latency, quality of service, etc.), which can be achieved in multi-layer SFC model. OSF can also be considered as a special SF. Secondly, we design a resource allocation algorithm, which we call OSF-oriented optical service scheduling algorithm. It is able to address multi-layer SFC optical service scheduling and provide comprehensive optical transmission service, while meeting multiple optical transmission requirements (e.g., bandwidth, latency, availability). Moreover, the algorithm exploits the concept of Auxiliary Graph. Finally, we compare our algorithm with the Baseline algorithm in simulation. And simulation results show that our algorithm achieves superior performance than Baseline algorithm in low traffic load condition.

Leveraging human decision making through the optimal management of centralized resources

NASA Astrophysics Data System (ADS)

Hyden, Paul; McGrath, Richard G.

2016-05-01

Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.

Using game theory for perceptual tuned rate control algorithm in video coding

NASA Astrophysics Data System (ADS)

Luo, Jiancong; Ahmad, Ishfaq

2005-03-01

This paper proposes a game theoretical rate control technique for video compression. Using a cooperative gaming approach, which has been utilized in several branches of natural and social sciences because of its enormous potential for solving constrained optimization problems, we propose a dual-level scheme to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks. At the frame level, the algorithm allocates target bits to frames based on their coding complexity. At the macroblock level, the algorithm distributes bits to macroblocks by defining a bargaining game. Macroblocks play cooperatively to compete for shares of resources (bits) to optimize their quantization scales while considering the Human Visual System"s perceptual property. Since the whole frame is an entity perceived by viewers, macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint. The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution. Another advantage is that it allows multi-objective optimization with multiple decision makers (macroblocks). The simulation results testify the algorithm"s ability to achieve accurate bit rate with good perceptual quality, and to maintain a stable buffer level.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

PubMed Central

2014-01-01

In order to overcome the shortcomings of existing medium access control (MAC) protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA) technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC) scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS) requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD) and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput. PMID:25126592

Combinatorial Optimization in Project Selection Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Dewi, Sari; Sawaluddin

2018-01-01

This paper discusses the problem of project selection in the presence of two objective functions that maximize profit and minimize cost and the existence of some limitations is limited resources availability and time available so that there is need allocation of resources in each project. These resources are human resources, machine resources, raw material resources. This is treated as a consideration to not exceed the budget that has been determined. So that can be formulated mathematics for objective function (multi-objective) with boundaries that fulfilled. To assist the project selection process, a multi-objective combinatorial optimization approach is used to obtain an optimal solution for the selection of the right project. It then described a multi-objective method of genetic algorithm as one method of multi-objective combinatorial optimization approach to simplify the project selection process in a large scope.

Energy-efficient routing, modulation and spectrum allocation in elastic optical networks

NASA Astrophysics Data System (ADS)

Tan, Yanxia; Gu, Rentao; Ji, Yuefeng

2017-07-01

With tremendous growth in bandwidth demand, energy consumption problem in elastic optical networks (EONs) becomes a hot topic with wide concern. The sliceable bandwidth-variable transponder in EON, which can transmit/receive multiple optical flows, was recently proposed to improve a transponder's flexibility and save energy. In this paper, energy-efficient routing, modulation and spectrum allocation (EE-RMSA) in EONs with sliceable bandwidth-variable transponder is studied. To decrease the energy consumption, we develop a Mixed Integer Linear Programming (MILP) model with corresponding EE-RMSA algorithm for EONs. The MILP model jointly considers the modulation format and optical grooming in the process of routing and spectrum allocation with the objective of minimizing the energy consumption. With the help of genetic operators, the EE-RMSA algorithm iteratively optimizes the feasible routing path, modulation format and spectrum resources solutions by explore the whole search space. In order to save energy, the optical-layer grooming strategy is designed to transmit the lightpath requests. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the blocking probability (BP) performance compare with the existing First-Fit-KSP algorithm, Iterative Flipping algorithm and EAMGSP algorithm especially in large network topology. Our results also demonstrate that the proposed EE-RMSA algorithm achieves almost the same performance as MILP on an 8-node network.

Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

NASA Astrophysics Data System (ADS)

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

2017-11-01

Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

Allocating operating room block time using historical caseload variability.

PubMed

Hosseini, Narges; Taaffe, Kevin M

2015-12-01

Operating room (OR) allocation and planning is one of the most important strategic decisions that OR managers face. The number of ORs that a hospital opens depends on the number of blocks that are allocated to the surgical groups, services, or individual surgeons, combined with the amount of open posting time (i.e., first come, first serve posting) that the hospital wants to provide. By allocating too few ORs, a hospital may turn away surgery demand whereas opening too many ORs could prove to be a costly decision. The traditional method of determining block frequency and size considers the average historical surgery demand for each group. However, given that there are penalties to the system for having too much or too little OR time allocated to a group, demand variability should play a role in determining the real OR requirement. In this paper we present an algorithm that allocates block time based on this demand variability, specifically accounting for both over-utilized time (time used beyond the block) and under-utilized time (time unused within the block). This algorithm provides a solution to the situation in which total caseload demand can be accommodated by the total OR resource set, in other words not in a capacity-constrained situation. We have found this scenario to be common among several regional healthcare providers with large OR suites and excess capacity. This algorithm could be used to adjust existing blocks or to assign new blocks to surgeons that did not previously have a block. We also have studied the effect of turnover time on the number of ORs that needs to be allocated. Numerical experiments based on real data from a large health-care provider indicate the opportunity to achieve over 2,900 hours of OR time savings through improved block allocations.

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Lemieux, George; Chester, Dave; Sonnenberg, Jerry

2015-05-01

Dynamic Spectrum Access (DSA) is widely seen as a solution to the problem of limited spectrum, because of its ability to adapt the operating frequency of a radio. Mobile Ad Hoc Networks (MANETs) can extend high-capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact, cognitive radio employs spectrum sensing to facilitate the identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, while secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate fair path use of the DSA-discovered links. Utilization of high-resolution geospatial data layers in RF propagation analysis is directly applicable. Random matrix theory (RMT) is useful in simulating network layer usage in nodes by a Wishart adjacency matrix. We use the Dijkstra algorithm for discovering ad hoc network node connection patterns. We present a method for analysts to dynamically allocate node-node path and link resources using fair division. User allocation of limited resources as a function of time must be dynamic and based on system fairness policies. The context of fair means that first available request for an asset is not envied as long as it is not yet allocated or tasked in order to prevent cycling of the system. This solution may also save money by offering a Pareto efficient repeatable process. We use a water fill queue algorithm to include Shapley value marginal contributions for allocation.

Multicriterion problem of allocation of resources in the heterogeneous distributed information processing systems

NASA Astrophysics Data System (ADS)

Antamoshkin, O. A.; Kilochitskaya, T. R.; Ontuzheva, G. A.; Stupina, A. A.; Tynchenko, V. S.

2018-05-01

This study reviews the problem of allocation of resources in the heterogeneous distributed information processing systems, which may be formalized in the form of a multicriterion multi-index problem with the linear constraints of the transport type. The algorithms for solution of this problem suggest a search for the entire set of Pareto-optimal solutions. For some classes of hierarchical systems, it is possible to significantly speed up the procedure of verification of a system of linear algebraic inequalities for consistency due to the reducibility of them to the stream models or the application of other solution schemes (for strongly connected structures) that take into account the specifics of the hierarchies under consideration.

A centre-free approach for resource allocation with lower bounds

NASA Astrophysics Data System (ADS)

Obando, Germán; Quijano, Nicanor; Rakoto-Ravalontsalama, Naly

2017-09-01

Since complexity and scale of systems are continuously increasing, there is a growing interest in developing distributed algorithms that are capable to address information constraints, specially for solving optimisation and decision-making problems. In this paper, we propose a novel method to solve distributed resource allocation problems that include lower bound constraints. The optimisation process is carried out by a set of agents that use a communication network to coordinate their decisions. Convergence and optimality of the method are guaranteed under some mild assumptions related to the convexity of the problem and the connectivity of the underlying graph. Finally, we compare our approach with other techniques reported in the literature, and we present some engineering applications.

Hybrid services efficient provisioning over the network coding-enabled elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Xin; Gu, Rentao; Ji, Yuefeng; Kavehrad, Mohsen

2017-03-01

As a variety of services have emerged, hybrid services have become more common in real optical networks. Although the elastic spectrum resource optimizations over the elastic optical networks (EONs) have been widely investigated, little research has been carried out on the hybrid services of the routing and spectrum allocation (RSA), especially over the network coding-enabled EON. We investigated the RSA for the unicast service and network coding-based multicast service over the network coding-enabled EON with the constraints of time delay and transmission distance. To address this issue, a mathematical model was built to minimize the total spectrum consumption for the hybrid services over the network coding-enabled EON under the constraints of time delay and transmission distance. The model guarantees different routing constraints for different types of services. The immediate nodes over the network coding-enabled EON are assumed to be capable of encoding the flows for different kinds of information. We proposed an efficient heuristic algorithm of the network coding-based adaptive routing and layered graph-based spectrum allocation algorithm (NCAR-LGSA). From the simulation results, NCAR-LGSA shows highly efficient performances in terms of the spectrum resources utilization under different network scenarios compared with the benchmark algorithms.

Updated System-Availability and Resource-Allocation Program

NASA Technical Reports Server (NTRS)

Viterna, Larry

2004-01-01

A second version of the Availability, Cost and Resource Allocation (ACARA) computer program has become available. The first version was reported in an earlier tech brief. To recapitulate: ACARA analyzes the availability, mean-time-between-failures of components, life-cycle costs, and scheduling of resources of a complex system of equipment. ACARA uses a statistical Monte Carlo method to simulate the failure and repair of components while complying with user-specified constraints on spare parts and resources. ACARA evaluates the performance of the system on the basis of a mathematical model developed from a block-diagram representation. The previous version utilized the MS-DOS operating system and could not be run by use of the most recent versions of the Windows operating system. The current version incorporates the algorithms of the previous version but is compatible with Windows and utilizes menus and a file-management approach typical of Windows-based software.

Strategic planning for disaster recovery with stochastic last mile distribution

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

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

2010-01-01

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

Data mining for multiagent rules, strategies, and fuzzy decision tree structure

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

2002-03-01

A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks

PubMed Central

Xia, Changqing; Kong, Linghe; Zeng, Peng

2017-01-01

Wireless sensor networks (WSNs) are widely applied in industrial manufacturing systems. By means of centralized control, the real-time requirement and reliability can be provided by WSNs in industrial production. Furthermore, many approaches reserve resources for situations in which the controller cannot perform centralized resource allocation. The controller assigns these resources as it becomes aware of when and where accidents have occurred. However, the reserved resources are limited, and such incidents are low-probability events. In addition, resource reservation may not be effective since the controller does not know when and where accidents will actually occur. To address this issue, we improve the reliability of scheduling for emergency tasks by proposing a method based on a stealing mechanism. In our method, an emergency task is transmitted by stealing resources allocated to regular flows. The challenges addressed in our work are as follows: (1) emergencies occur only occasionally, but the industrial system must deliver the corresponding flows within their deadlines when they occur; (2) we wish to minimize the impact of emergency flows by reducing the number of stolen flows. The contributions of this work are two-fold: (1) we first define intersections and blocking as new characteristics of flows; and (2) we propose a series of distributed routing algorithms to improve the schedulability and to reduce the impact of emergency flows. We demonstrate that our scheduling algorithm and analysis approach are better than the existing ones by extensive simulations. PMID:28726738

Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

PubMed Central

Jin, Yichao; Vural, Serdar; Gluhak, Alexander; Moessner, Klaus

2013-01-01

This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines. PMID:24135992

77 FR 37944 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-25

... same class as an affiliate if CBOE uses in that class an allocation algorithm that allocates electronic... in a particular options class an allocation algorithm that does not allocate electronic trades, in... bid or offer. Unlike the CBOE, the ISE allocation algorithm does not provide for the potential...

Reorienting the HIV response in Niger toward sex work interventions: from better evidence to targeted and expanded practice.

PubMed

Fraser, Nicole; Kerr, Cliff C; Harouna, Zakou; Alhousseini, Zeinabou; Cheikh, Nejma; Gray, Richard; Shattock, Andrew; Wilson, David P; Haacker, Markus; Shubber, Zara; Masaki, Emiko; Karamoko, Djibrilla; Görgens, Marelize

2015-03-01

Niger's low-burden, sex-work-driven HIV epidemic is situated in a context of high economic and demographic growth. Resource availability of HIV/AIDS has been decreasing recently. In 2007-2012, only 1% of HIV expenditure was for sex work interventions, but an estimated 37% of HIV incidence was directly linked to sex work in 2012. The Government of Niger requested assistance to determine an efficient allocation of its HIV resources and to strengthen HIV programming for sex workers. Optima, an integrated epidemiologic and optimization tool, was applied using local HIV epidemic, demographic, programmatic, expenditure, and cost data. A mathematical optimization algorithm was used to determine the best resource allocation for minimizing HIV incidence and disability-adjusted life years (DALYs) over 10 years. Efficient allocation of the available HIV resources, to minimize incidence and DALYs, would increase expenditure for sex work interventions from 1% to 4%-5%, almost double expenditure for antiretroviral treatment and for the prevention of mother-to-child transmission, and reduce expenditure for HIV programs focusing on the general population. Such an investment could prevent an additional 12% of new infections despite a budget of less than half of the 2012 reference year. Most averted infections would arise from increased funding for sex work interventions. This allocative efficiency analysis makes the case for increased investment in sex work interventions to minimize future HIV incidence and DALYs. Optimal HIV resource allocation combined with improved program implementation could have even greater HIV impact. Technical assistance is being provided to make the money invested in sex work programs work better and help Niger to achieve a cost-effective and sustainable HIV response.

Multi-agent systems design for aerospace applications

NASA Astrophysics Data System (ADS)

Waslander, Steven L.

2007-12-01

Engineering systems with independent decision makers are becoming increasingly prevalent and present many challenges in coordinating actions to achieve systems goals. In particular, this work investigates the applications of air traffic flow control and autonomous vehicles as motivation to define algorithms that allow agents to agree to safe, efficient and equitable solutions in a distributed manner. To ensure system requirements will be satisfied in practice, each method is evaluated for a specific model of agent behavior, be it cooperative or non-cooperative. The air traffic flow control problem is investigated from the point of view of the airlines, whose costs are directly affected by resource allocation decisions made by the Federal Aviation Administration in order to mitigate traffic disruptions caused by weather. Airlines are first modeled as cooperative, and a distributed algorithm is presented with various global cost metrics which balance efficient and equitable use of resources differently. Next, a competitive airline model is assumed and two market mechanisms are developed for allocating contested airspace resources. The resource market mechanism provides a solution for which convergence to an efficient solution can be guaranteed, and each airline will improve on the solution that would occur without its inclusion in the decision process. A lump-sum market is then introduced as an alternative mechanism, for which efficiency loss bounds exist if airlines attempt to manipulate prices. Initial convergence results for lump-sum markets are presented for simplified problems with a single resource. To validate these algorithms, two air traffic flow models are developed which extend previous techniques, the first a convenient convex model made possible by assuming constant velocity flow, and the second a more complex flow model with full inflow, velocity and rerouting control. Autonomous vehicle teams are envisaged for many applications including mobile sensing and search and rescue. To enable these high-level applications, multi-vehicle collision avoidance is solved using a cooperative, decentralized algorithm. For the development of coordination algorithms for autonomous vehicles, the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) is presented. This testbed provides significant advantages over other aerial testbeds due to its small size and low maintenance requirements.

An expert fitness diagnosis system based on elastic cloud computing.

PubMed

Tseng, Kevin C; Wu, Chia-Chuan

2014-01-01

This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service.

Column generation algorithms for virtual network embedding in flexi-grid optical networks.

PubMed

Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe

2018-04-16

Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.

The implement of Talmud property allocation algorithm based on graphic point-segment way

NASA Astrophysics Data System (ADS)

Cen, Haifeng

2017-04-01

Under the guidance of the Talmud allocation scheme's theory, the paper analyzes the algorithm implemented process via the perspective of graphic point-segment way, and designs the point-segment way's Talmud property allocation algorithm. Then it uses Java language to implement the core of allocation algorithm, by using Android programming to build a visual interface.

Allocating Tactical High-Performance Computer (HPC) Resources to Offloaded Computation in Battlefield Scenarios

DTIC Science & Technology

2013-12-01

authors present a Computing on Dissemination with predictable contacts ( pCoD ) algorithm, since it is impossible to reserve task execution time in advance...Computing While Charging DAG Directed Acyclic Graph 18 TTL Time-to-live pCoD Predictable contacts CoD Computing on Dissemination upCoD Unpredictable

Dynamic resource allocation scheme for distributed heterogeneous computer systems

NASA Technical Reports Server (NTRS)

Liu, Howard T. (Inventor); Silvester, John A. (Inventor)

1991-01-01

This invention relates to a resource allocation in computer systems, and more particularly, to a method and associated apparatus for shortening response time and improving efficiency of a heterogeneous distributed networked computer system by reallocating the jobs queued up for busy nodes to idle, or less-busy nodes. In accordance with the algorithm (SIDA for short), the load-sharing is initiated by the server device in a manner such that extra overhead in not imposed on the system during heavily-loaded conditions. The algorithm employed in the present invention uses a dual-mode, server-initiated approach. Jobs are transferred from heavily burdened nodes (i.e., over a high threshold limit) to low burdened nodes at the initiation of the receiving node when: (1) a job finishes at a node which is burdened below a pre-established threshold level, or (2) a node is idle for a period of time as established by a wakeup timer at the node. The invention uses a combination of the local queue length and the local service rate ratio at each node as the workload indicator.

Amoeba-inspired Tug-of-War algorithms for exploration-exploitation dilemma in extended Bandit Problem.

PubMed

Aono, Masashi; Kim, Song-Ju; Hara, Masahiko; Munakata, Toshinori

2014-03-01

The true slime mold Physarum polycephalum, a single-celled amoeboid organism, is capable of efficiently allocating a constant amount of intracellular resource to its pseudopod-like branches that best fit the environment where dynamic light stimuli are applied. Inspired by the resource allocation process, the authors formulated a concurrent search algorithm, called the Tug-of-War (TOW) model, for maximizing the profit in the multi-armed Bandit Problem (BP). A player (gambler) of the BP should decide as quickly and accurately as possible which slot machine to invest in out of the N machines and faces an "exploration-exploitation dilemma." The dilemma is a trade-off between the speed and accuracy of the decision making that are conflicted objectives. The TOW model maintains a constant intracellular resource volume while collecting environmental information by concurrently expanding and shrinking its branches. The conservation law entails a nonlocal correlation among the branches, i.e., volume increment in one branch is immediately compensated by volume decrement(s) in the other branch(es). Owing to this nonlocal correlation, the TOW model can efficiently manage the dilemma. In this study, we extend the TOW model to apply it to a stretched variant of BP, the Extended Bandit Problem (EBP), which is a problem of selecting the best M-tuple of the N machines. We demonstrate that the extended TOW model exhibits better performances for 2-tuple-3-machine and 2-tuple-4-machine instances of EBP compared with the extended versions of well-known algorithms for BP, the ϵ-Greedy and SoftMax algorithms, particularly in terms of its short-term decision-making capability that is essential for the survival of the amoeba in a hostile environment. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Application of a COTS Resource Optimization Framework to the SSN Sensor Tasking Domain - Part I: Problem Definition

NASA Astrophysics Data System (ADS)

Tran, T.

With the onset of the SmallSat era, the RSO catalog is expected to see continuing growth in the near future. This presents a significant challenge to the current sensor tasking of the SSN. The Air Force is in need of a sensor tasking system that is robust, efficient, scalable, and able to respond in real-time to interruptive events that can change the tracking requirements of the RSOs. Furthermore, the system must be capable of using processed data from heterogeneous sensors to improve tasking efficiency. The SSN sensor tasking can be regarded as an economic problem of supply and demand: the amount of tracking data needed by each RSO represents the demand side while the SSN sensor tasking represents the supply side. As the number of RSOs to be tracked grows, demand exceeds supply. The decision-maker is faced with the problem of how to allocate resources in the most efficient manner. Braxton recently developed a framework called Multi-Objective Resource Optimization using Genetic Algorithm (MOROUGA) as one of its modern COTS software products. This optimization framework took advantage of the maturing technology of evolutionary computation in the last 15 years. This framework was applied successfully to address the resource allocation of an AFSCN-like problem. In any resource allocation problem, there are five key elements: (1) the resource pool, (2) the tasks using the resources, (3) a set of constraints on the tasks and the resources, (4) the objective functions to be optimized, and (5) the demand levied on the resources. In this paper we explain in detail how the design features of this optimization framework are directly applicable to address the SSN sensor tasking domain. We also discuss our validation effort as well as present the result of the AFSCN resource allocation domain using a prototype based on this optimization framework.

Distributed Multiple Access Control for the Wireless Mesh Personal Area Networks

NASA Astrophysics Data System (ADS)

Park, Moo Sung; Lee, Byungjoo; Rhee, Seung Hyong

Mesh networking technologies for both high-rate and low-rate wireless personal area networks (WPANs) are under development by several standardization bodies. They are considering to adopt distributed TDMA MAC protocols to provide seamless user mobility as well as a good peer-to-peer QoS in WPAN mesh. It has been, however, pointed out that the absence of a central controller in the wireless TDMA MAC may cause a severe performance degradation: e. g., fair allocation, service differentiation, and admission control may be hard to achieve or can not be provided. In this paper, we suggest a new framework of resource allocation for the distributed MAC protocols in WPANs. Simulation results show that our algorithm achieves both a fair resource allocation and flexible service differentiations in a fully distributed way for mesh WPANs where the devices have high mobility and various requirements. We also provide an analytical modeling to discuss about its unique equilibrium and to compute the lengths of reserved time slots at the stable point.

Optimum Allocation of Water to the Cultivation Farms Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Saeidian, B.; Saadi Mesgari, M.; Ghodousi, M.

2015-12-01

The water scarcity crises in the world and specifically in Iran, requires the proper management of this valuable resource. According to the official reports, around 90 percent of the water in Iran is used for agriculture. Therefore, the adequate management and usage of water in this section can help significantly to overcome the above crises. The most important aspect of agricultural water management is related to the irrigation planning, which is basically an allocation problem. The proper allocation of water to the farms is not a simple and trivial problem, because of the limited amount of available water, the effect of different parameters, nonlinear characteristics of the objective function, and the wideness of the solution space. Usually To solve such complex problems, a meta-heuristic method such as genetic algorithm could be a good candidate. In this paper, Genetic Algorithm (GA) is used for the allocation of different amount of water to a number of farms. In this model, the amount of water transferable using canals of level one, in one period of irrigation is specified. In addition, the amount of water required by each farm is calculated using crop type, stage of crop development, and other parameters. Using these, the water production function of each farm is determined. Then, using the water production function, farm areas, and the revenue and cost of each crop type, the objective function is calculated. This objective function is used by GA for the allocation of water to the farms. The objective function is defined such that the economical profit extracted from all farms is maximized. Moreover, the limitation related to the amount of available water is considered as a constraint. In general, the total amount of allocated water should be less than the finally available water (the water transferred trough the level one canals). Because of the intensive scarcity of water, the deficit irrigation method are considered. In this method, the planning is on the basis of the optimum and limited allocation of water, and not on the basis of the each crop water requirement. According to the available literature, in the condition of water scarcity, the implementation of deficit irrigation strategy results in higher economical income. The main difference of this research with others is the allocation of water to the farms. Whilst, most of similar researches concentrate on the allocation of water to different water consumption sections (such as agriculture, industry etc.), networks and crops. Using the GA for the optimization of the water allocation, proper solutions were generated that maximize the total economical income in the entire study area. In addition, although the search space was considerably wide, the results of the implementation showed an adequate convergence speed. The repeatability test of the algorithm also proved that the algorithm is reasonably stable. In general the usage of GA algorithm can be considered as an efficient and trustable method for such irrigation planning problems. By optimum allocation of the water to the farms with different areas and crop types, and considering the deficit irrigation method, the general income of the entire area can be improved substantially.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

NASA Astrophysics Data System (ADS)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

Range wise busy checking 2-way imbalanced algorithm for cloudlet allocation in cloud environment

NASA Astrophysics Data System (ADS)

Alanzy, Mohammed; Latip, Rohaya; Muhammed, Abdullah

2018-05-01

Cloud computing considers as a new business paradigm and a popular platform over the last few years. Many organizations, agencies, and departments consider responsible tasks time and tasks needed to be accomplished as soon as possible. These agencies counter IT issues due to the massive arise of data, applications, and solution scopes. Currently, the main issue related with the cloud is the way of making the environment of the cloud computing more qualified, and this way needs a competent allocation strategy of the cloudlet, Thus, there are huge number of studies conducted with regards to this matter that sought to assign the cloudlets to VMs or resources by variety of strategies. In this paper we have proposed range wise busy checking 2-way imbalanced Algorithm in cloud computing. Compare to other methods, it decreases the completion time to finish tasks’ execution, it is considered the fundamental part to enhance the system performance such as the makespan. This algorithm was simulated using Cloudsim to give more opportunity to the higher VM speed to accommodate more Cloudlets in its local queue without considering the threshold balance condition. The simulation result shows that the average makespan time is lesser compare to the previous cloudlet allocation strategy.

System identification of an unmanned quadcopter system using MRAN neural

NASA Astrophysics Data System (ADS)

Pairan, M. F.; Shamsudin, S. S.

2017-12-01

This project presents the performance analysis of the radial basis function neural network (RBF) trained with Minimal Resource Allocating Network (MRAN) algorithm for real-time identification of quadcopter. MRAN’s performance is compared with the RBF with Constant Trace algorithm for 2500 input-output pair data sampling. MRAN utilizes adding and pruning hidden neuron strategy to obtain optimum RBF structure, increase prediction accuracy and reduce training time. The results indicate that MRAN algorithm produces fast training time and more accurate prediction compared with standard RBF. The model proposed in this paper is capable of identifying and modelling a nonlinear representation of the quadcopter flight dynamics.

Dealing with equality and benefit for water allocation in a lake watershed: A Gini-coefficient based stochastic optimization approach

NASA Astrophysics Data System (ADS)

Dai, C.; Qin, X. S.; Chen, Y.; Guo, H. C.

2018-06-01

A Gini-coefficient based stochastic optimization (GBSO) model was developed by integrating the hydrological model, water balance model, Gini coefficient and chance-constrained programming (CCP) into a general multi-objective optimization modeling framework for supporting water resources allocation at a watershed scale. The framework was advantageous in reflecting the conflicting equity and benefit objectives for water allocation, maintaining the water balance of watershed, and dealing with system uncertainties. GBSO was solved by the non-dominated sorting Genetic Algorithms-II (NSGA-II), after the parameter uncertainties of the hydrological model have been quantified into the probability distribution of runoff as the inputs of CCP model, and the chance constraints were converted to the corresponding deterministic versions. The proposed model was applied to identify the Pareto optimal water allocation schemes in the Lake Dianchi watershed, China. The optimal Pareto-front results reflected the tradeoff between system benefit (αSB) and Gini coefficient (αG) under different significance levels (i.e. q) and different drought scenarios, which reveals the conflicting nature of equity and efficiency in water allocation problems. A lower q generally implies a lower risk of violating the system constraints and a worse drought intensity scenario corresponds to less available water resources, both of which would lead to a decreased system benefit and a less equitable water allocation scheme. Thus, the proposed modeling framework could help obtain the Pareto optimal schemes under complexity and ensure that the proposed water allocation solutions are effective for coping with drought conditions, with a proper tradeoff between system benefit and water allocation equity.

An intelligent allocation algorithm for parallel processing

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Analysis of labor employment assessment on production machine to minimize time production

NASA Astrophysics Data System (ADS)

Hernawati, Tri; Suliawati; Sari Gumay, Vita

2018-03-01

Every company both in the field of service and manufacturing always trying to pass efficiency of it’s resource use. One resource that has an important role is labor. Labor has different efficiency levels for different jobs anyway. Problems related to the optimal allocation of labor that has different levels of efficiency for different jobs are called assignment problems, which is a special case of linear programming. In this research, Analysis of Labor Employment Assesment on Production Machine to Minimize Time Production, in PT PDM is done by using Hungarian algorithm. The aim of the research is to get the assignment of optimal labor on production machine to minimize time production. The results showed that the assignment of existing labor is not suitable because the time of completion of the assignment is longer than the assignment by using the Hungarian algorithm. By applying the Hungarian algorithm obtained time savings of 16%.

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

NASA Astrophysics Data System (ADS)

Opadiji, Jayeola Femi; Kaihara, Toshiya

We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

Site Selection and Resource Allocation of Oil Spill Emergency Base for Offshore Oil Facilities

NASA Astrophysics Data System (ADS)

Li, Yunbin; Liu, Jingxian; Wei, Lei; Wu, Weihuang

2018-02-01

Based on the analysis of the historical data about oil spill accidents in the Bohai Sea, this paper discretizes oil spilled source into a limited number of spill points. According to the probability of oil spill risk, the demand for salvage forces at each oil spill point is evaluated. Aiming at the specific location of the rescue base around the Bohai Sea, a cost-benefit analysis is conducted to determine the total cost of disasters for each rescue base. Based on the relationship between the oil spill point and the rescue site, a multi-objective optimization location model for the oil spill rescue base in the Bohai Sea region is established. And the genetic algorithm is used to solve the optimization problem, and determine the emergency rescue base optimization program and emergency resources allocation ratio.

Multiple Leader Candidate and Competitive Position Allocation for Robust Formation against Member Robot Faults

PubMed Central

Kwon, Ji-Wook; Kim, Jin Hyo; Seo, Jiwon

2015-01-01

This paper proposes a Multiple Leader Candidate (MLC) structure and a Competitive Position Allocation (CPA) algorithm which can be applicable for various applications including environmental sensing. Unlike previous formation structures such as virtual-leader and actual-leader structures with position allocation including a rigid allocation and an optimization based allocation, the formation employing the proposed MLC structure and CPA algorithm is robust against the fault (or disappearance) of the member robots and reduces the entire cost. In the MLC structure, a leader of the entire system is chosen among leader candidate robots. The CPA algorithm is the decentralized position allocation algorithm that assigns the robots to the vertex of the formation via the competition of the adjacent robots. The numerical simulations and experimental results are included to show the feasibility and the performance of the multiple robot system employing the proposed MLC structure and the CPA algorithm. PMID:25954956

On inclusion of water resource management in Earth system models - Part 1: Problem definition and representation of water demand

NASA Astrophysics Data System (ADS)

Nazemi, A.; Wheater, H. S.

2015-01-01

Human activities have caused various changes to the Earth system, and hence the interconnections between human activities and the Earth system should be recognized and reflected in models that simulate Earth system processes. One key anthropogenic activity is water resource management, which determines the dynamics of human-water interactions in time and space and controls human livelihoods and economy, including energy and food production. There are immediate needs to include water resource management in Earth system models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human-water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Due to the importance of water resource management in determining the future of the global water and climate cycles, the World Climate Research Program's Global Energy and Water Exchanges project (WRCP-GEWEX) has recently identified gaps in describing human-water interactions as one of the grand challenges in Earth system modeling (GEWEX, 2012). Here, we divide water resource management into two interdependent elements, related firstly to water demand and secondly to water supply and allocation. In this paper, we survey the current literature on how various components of water demand have been included in large-scale models, in particular land surface and global hydrological models. Issues of water supply and allocation are addressed in a companion paper. The available algorithms to represent the dominant demands are classified based on the demand type, mode of simulation and underlying modeling assumptions. We discuss the pros and cons of available algorithms, address various sources of uncertainty and highlight limitations in current applications. We conclude that current capability of large-scale models to represent human water demands is rather limited, particularly with respect to future projections and coupled land-atmospheric simulations. To fill these gaps, the available models, algorithms and data for representing various water demands should be systematically tested, intercompared and improved. In particular, human water demands should be considered in conjunction with water supply and allocation, particularly in the face of water scarcity and unknown future climate.

Research on allocation efficiency of the daisy chain allocation algorithm

NASA Astrophysics Data System (ADS)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

PubMed Central

Gao, Yuan; Zhou, Weigui; Ao, Hong; Chu, Jian; Zhou, Quan; Zhou, Bo; Wang, Kang; Li, Yi; Xue, Peng

2016-01-01

With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives. PMID:27077865

Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

PubMed Central

Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

2015-01-01

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

Knowledge discovery through games and game theory

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D.

2001-03-01

A fuzzy logic based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. The initial version of the algorithm was optimized using a genetic algorithm employing fitness functions constructed based on expertise. A new approach is being explored that involves embedding the resource manager in a electronic game environment. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the database as required. The game allows easy evaluation of the information mined in the second step. The measure of effectiveness (MOE) for re-optimization is discussed. The mined information is extremely valuable as shown through demanding scenarios.

Research on schedulers for astronomical observatories

NASA Astrophysics Data System (ADS)

Colome, Josep; Colomer, Pau; Guàrdia, Josep; Ribas, Ignasi; Campreciós, Jordi; Coiffard, Thierry; Gesa, Lluis; Martínez, Francesc; Rodler, Florian

2012-09-01

The main task of a scheduler applied to astronomical observatories is the time optimization of the facility and the maximization of the scientific return. Scheduling of astronomical observations is an example of the classical task allocation problem known as the job-shop problem (JSP), where N ideal tasks are assigned to M identical resources, while minimizing the total execution time. A problem of higher complexity, called the Flexible-JSP (FJSP), arises when the tasks can be executed by different resources, i.e. by different telescopes, and it focuses on determining a routing policy (i.e., which machine to assign for each operation) other than the traditional scheduling decisions (i.e., to determine the starting time of each operation). In most cases there is no single best approach to solve the planning system and, therefore, various mathematical algorithms (Genetic Algorithms, Ant Colony Optimization algorithms, Multi-Objective Evolutionary algorithms, etc.) are usually considered to adapt the application to the system configuration and task execution constraints. The scheduling time-cycle is also an important ingredient to determine the best approach. A shortterm scheduler, for instance, has to find a good solution with the minimum computation time, providing the system with the capability to adapt the selected task to varying execution constraints (i.e., environment conditions). We present in this contribution an analysis of the task allocation problem and the solutions currently in use at different astronomical facilities. We also describe the schedulers for three different projects (CTA, CARMENES and TJO) where the conclusions of this analysis are applied to develop a suitable routine.

Data location-aware job scheduling in the grid. Application to the GridWay metascheduler

NASA Astrophysics Data System (ADS)

Delgado Peris, Antonio; Hernandez, Jose; Huedo, Eduardo; Llorente, Ignacio M.

2010-04-01

Grid infrastructures constitute nowadays the core of the computing facilities of the biggest LHC experiments. These experiments produce and manage petabytes of data per year and run thousands of computing jobs every day to process that data. It is the duty of metaschedulers to allocate the tasks to the most appropriate resources at the proper time. Our work reviews the policies that have been proposed for the scheduling of grid jobs in the context of very data-intensive applications. We indicate some of the practical problems that such models will face and describe what we consider essential characteristics of an optimum scheduling system: aim to minimise not only job turnaround time but also data replication, flexibility to support different virtual organisation requirements and capability to coordinate the tasks of data placement and job allocation while keeping their execution decoupled. These ideas have guided the development of an enhanced prototype for GridWay, a general purpose metascheduler, part of the Globus Toolkit and member of the EGEE's RESPECT program. Current GridWay's scheduling algorithm is unaware of data location. Our prototype makes it possible for job requests to set data needs not only as absolute requirements but also as functions for resource ranking. As our tests show, this makes it more flexible than currently used resource brokers to implement different data-aware scheduling algorithms.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks.

PubMed

Devi, D Chitra; Uthariaraj, V Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

PubMed Central

Devi, D. Chitra; Uthariaraj, V. Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods. PMID:26955656

Mathematical models of functioning and allocation indicators of road-transport complex resources in the fuel and raw materials region

NASA Astrophysics Data System (ADS)

Buyvis, V. A.; Novichikhin, A. V.; Temlyantsev, M. V.

2017-09-01

A number of features of coal industry functioning was determined for the conditions of Kemerovo region, and the specifics of planning and organization of coal transportation were revealed. The analysis of indicators of motor and railway types of transport in the process of coal transportation was executed. The necessity of improving the tools of coal products transportation in the modern conditions is substantiated. Specific features of functioning of a road-transport complex in the fuel and raw material region (on the example of Kemerovo region) are determined. The modern scientific and applied problems of functioning and allocation of the road-transport complex resources are identified. To justify the management decisions on the development and improvement of road-transport complex a set of indicators are proposed: infrastructural, transportation performance, operating, social and economic. Mathematical models of indicators are recommended for formulation and justification of decisions made during operational and strategic planning of development, evaluation and development of algorithms of functioning and allocation of road-transport sector in Kemerovo region in the future.

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

PubMed Central

Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

2016-01-01

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical modeling. PMID:27044039

Smart LED allocation scheme for efficient multiuser visible light communication networks.

PubMed

Sewaiwar, Atul; Tiwari, Samrat Vikramaditya; Chung, Yeon Ho

2015-05-18

In a multiuser bidirectional visible light communication (VLC), a large number of LEDs or an LED array needs to be allocated in an efficient manner to ensure sustainable data rate and link quality. Moreover, in order to support an increasing or decreasing number of users in the network, the LED allocation is required to be performed dynamically. In this paper, a novel smart LED allocation scheme for efficient multiuser VLC networks is presented. The proposed scheme allocates RGB LEDs to multiple users in a dynamic and efficient fashion, while satisfying illumination requirements in an indoor environment. The smart LED array comprised of RGB LEDs is divided into sectors according to the location of the users. The allocated sectors then provide optical power concentration toward the users for efficient and reliable data transmission. An algorithm for the dynamic allocation of the LEDs is also presented. To verify its effective resource allocation feature of the proposed scheme, simulations were performed. It is found that the proposed smart LED allocation scheme provides the effect of optical beamforming toward individual users, thereby increasing the collective power concentration of the optical signals on the desirable users and resulting in significantly increased data rate, while ensuring sufficient illumination in a multiuser VLC environment.

Optimization of over-provisioned clouds

NASA Astrophysics Data System (ADS)

Balashov, N.; Baranov, A.; Korenkov, V.

2016-09-01

The functioning of modern applications in cloud-centers is characterized by a huge variety of computational workloads generated. This causes uneven workload distribution and as a result leads to ineffective utilization of cloud-centers' hardware. The proposed article addresses the possible ways to solve this issue and demonstrates that it is a matter of necessity to optimize cloud-centers' hardware utilization. As one of the possible ways to solve the problem of the inefficient resource utilization in heterogeneous cloud-environments an algorithm of dynamic re-allocation of virtual resources is suggested.

Improving Learning Performance Through Rational Resource Allocation

NASA Technical Reports Server (NTRS)

Gratch, J.; Chien, S.; DeJong, G.

1994-01-01

This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning cost and show that the problem of efficient learning can be cast as a resource optimization problem. Solutions found in this way can be significantly more efficient than the best solutions that do not account for these factors. We introduce a heuristic learning algorithm that approximately solves this optimization problem and document its performance improvements on synthetic and real-world problems.

76 FR 13688 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-14

... class-by-class basis which electronic allocation algorithm \\6\\ would apply for rotations. Currently Rule... opening price (with multiple quotes and orders being ranked in accordance with the allocation algorithm in... and quotes ranked in accordance with the allocation algorithm in effect for the class). Any remaining...

Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization

PubMed Central

Ling, Teresa Wai Ching; Yeung, Wing Kwan

2017-01-01

This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources. PMID:29104748

Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization.

PubMed

Lin, Carrie Ka Yuk; Ling, Teresa Wai Ching; Yeung, Wing Kwan

2017-01-01

This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

PubMed

Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo

2017-10-28

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

Trading a Problem-solving Task

NASA Astrophysics Data System (ADS)

Matsubara, Shigeo

This paper focuses on a task allocation problem, especially cases where the task is to find a solution in a search problem or a constraint satisfaction problem. If the search problem is hard to solve, a contractor may fail to find a solution. Here, the more computational resources such as the CPU time the contractor invests in solving the search problem, the more a solution is likely to be found. This brings about a new problem that a contractee has to find an appropriate level of the quality in a task achievement as well as to find an efficient allocation of a task among contractors. For example, if the contractee asks the contractor to find a solution with certainty, the payment from the contractee to the contractor may exceed the contractee's benefit from obtaining a solution, which discourages the contractee from trading a task. However, solving this problem is difficult because the contractee cannot ascertain the contractor's problem-solving ability such as the amount of available resources and knowledge (e.g. algorithms, heuristics) or monitor what amount of resources are actually invested in solving the allocated task. To solve this problem, we propose a task allocation mechanism that is able to choose an appropriate level of the quality in a task achievement and prove that this mechanism guarantees that each contractor reveals its true information. Moreover, we show that our mechanism can increase the contractee's utility compared with a simple auction mechanism by using computer simulation.

Complexity Analysis and Algorithms for Optimal Resource Allocation in Wireless Networks

DTIC Science & Technology

2012-09-01

independent orthogonal signaling such as OFDM . The general formulation will exploit the concept of ‘interference alignment’ which is known to provide...substantial rate gain over OFDM signalling for general interference channels. We have successfully analyzed the complexity to characterize the optimal...categories: PaperReceived Gennady Lyubeznik, Zhi-Quan Luo, Meisam Razaviyayn. On the degrees of freedom achievable through interference alignment in a MIMO

Dynamic Airspace Configuration

NASA Technical Reports Server (NTRS)

Bloem, Michael J.

2014-01-01

In air traffic management systems, airspace is partitioned into regions in part to distribute the tasks associated with managing air traffic among different systems and people. These regions, as well as the systems and people allocated to each, are changed dynamically so that air traffic can be safely and efficiently managed. It is expected that new air traffic control systems will enable greater flexibility in how airspace is partitioned and how resources are allocated to airspace regions. In this talk, I will begin by providing an overview of some previous work and open questions in Dynamic Airspace Configuration research, which is concerned with how to partition airspace and assign resources to regions of airspace. For example, I will introduce airspace partitioning algorithms based on clustering, integer programming optimization, and computational geometry. I will conclude by discussing the development of a tablet-based tool that is intended to help air traffic controller supervisors configure airspace and controllers in current operations.

Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things.

PubMed

Sun, Yanjing; Guo, Yiyu; Li, Song; Wu, Dapeng; Wang, Bin

2018-05-15

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel

PubMed Central

Sakin, Sayef Azad; Alamri, Atif; Tran, Nguyen H.

2017-01-01

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies. PMID:29215591

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel.

PubMed

Sakin, Sayef Azad; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Alamri, Atif; Tran, Nguyen H; Fortino, Giancarlo

2017-12-07

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

76 FR 59470 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-26

... allocation algorithm shall apply for COB and/or COA executions on a class-by-class basis, subject to certain conditions. Currently, as described in more detail below, the allocation algorithms for COB and COA default to the allocation algorithms in effect for a given options class. As proposed, the rule change would...

Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Zhao, Xiaohui; Liang, Cong; Ding, Xu

2017-01-01

In cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.

Particle swarm optimization based space debris surveillance network scheduling

NASA Astrophysics Data System (ADS)

Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao

2017-02-01

The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.

A general optimality criteria algorithm for a class of engineering optimization problems

NASA Astrophysics Data System (ADS)

Belegundu, Ashok D.

2015-05-01

An optimality criteria (OC)-based algorithm for optimization of a general class of nonlinear programming (NLP) problems is presented. The algorithm is only applicable to problems where the objective and constraint functions satisfy certain monotonicity properties. For multiply constrained problems which satisfy these assumptions, the algorithm is attractive compared with existing NLP methods as well as prevalent OC methods, as the latter involve computationally expensive active set and step-size control strategies. The fixed point algorithm presented here is applicable not only to structural optimization problems but also to certain problems as occur in resource allocation and inventory models. Convergence aspects are discussed. The fixed point update or resizing formula is given physical significance, which brings out a strength and trim feature. The number of function evaluations remains independent of the number of variables, allowing the efficient solution of problems with large number of variables.

Comparison of Provider Types Who Performed Prehospital Lifesaving Interventions: A Prospective Study

DTIC Science & Technology

2014-12-01

In less than 2 hours, 15 critically ill children were triaged and admitted to the PICU or surge spaces. Conclusions:Identified strengths included...details increasing telemedicine uti - lization during a 4 year period and outlines program structural changes that improved utilization. Methods: The study...population survival. CSC ICU resource- allocation algorithms (ALGs) exist for adults. Our goal was to evaluate a CSC pandemic ALG for children . Methods

Factors influencing resource allocation decisions and equity in the health system of Ghana.

PubMed

Asante, A D; Zwi, A B

2009-05-01

Allocation of financial resources in the health sector is often seen as a formula-driven activity. However, the decision to allocate a certain amount of resources to a particular health jurisdiction or facility may be based on a broader range of factors, sometimes not reflected in the existing resource allocation formula. This study explores the 'other' factors that influence the equity of resource allocation in the health system of Ghana. The extent to which these factors are, or can be, accounted for in the resource allocation process is analysed. An exploratory design focusing on different levels of the health system and diverse stakeholders. Data were gathered through semi-structured qualitative interviews with health authorities at national, regional and district levels, and with donor representatives and local government officials in 2003 and 2004. The availability of human resources for health, local capacity to utilize funds, donor involvement in the health sector, and commitment to promote equity have considerable influence on resource allocation decisions and affect the equity of funding allocations. However, these factors are not accounted for adequately in the resource allocation process. This study highlights the need for a more transparent resource allocation system in Ghana based on needs, and takes into account key issues such as capacity constraints, the inequitable human resource distribution and donor-earmarked funding.

Optimal management of a multispecies shorebird flyway under sea-level rise.

PubMed

Iwamura, Takuya; Fuller, Richard A; Possingham, Hugh P

2014-12-01

Every year, millions of migratory shorebirds fly through the East Asian-Australasian Flyway between their arctic breeding grounds and Australasia. This flyway includes numerous coastal wetlands in Asia and the Pacific that are used as stopover sites where birds rest and feed. Loss of a few important stopover sites through sea-level rise (SLR) could cause sudden population declines. We formulated and solved mathematically the problem of how to identify the most important stopover sites to minimize losses of bird populations across flyways by conserving land that facilitates upshore shifts of tidal flats in response to SLR. To guide conservation investment that minimizes losses of migratory bird populations during migration, we developed a spatially explicit flyway model coupled with a maximum flow algorithm. Migratory routes of 10 shorebird taxa were modeled in a graph theoretic framework by representing clusters of important wetlands as nodes and the number of birds flying between 2 nodes as edges. We also evaluated several resource allocation algorithms that required only partial information on flyway connectivity (node strategy, based on the impacts of SLR at nodes; habitat strategy, based on habitat change at sites; population strategy, based on population change at sites; and random investment). The resource allocation algorithms based on flyway information performed on average 15% better than simpler allocations based on patterns of habitat loss or local bird counts. The Yellow Sea region stood out as the most important priority for effective conservation of migratory shorebirds, but investment in this area alone will not ensure the persistence of species across the flyway. The spatial distribution of conservation investments differed enormously according to the severity of SLR and whether information about flyway connectivity was used to guide the prioritizations. With the rapid ongoing loss of coastal wetlands globally, our method provides insight into efficient conservation planning for migratory species. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.

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.

Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor

PubMed Central

Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

2014-01-01

Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm. PMID:25152925

Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.

PubMed

Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

2014-01-01

Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.

From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers.

PubMed

Nakrani, Sunil; Tovey, Craig

2007-12-01

An Internet hosting center hosts services on its server ensemble. The center must allocate servers dynamically amongst services to maximize revenue earned from hosting fees. The finite server ensemble, unpredictable request arrival behavior and server reallocation cost make server allocation optimization difficult. Server allocation closely resembles honeybee forager allocation amongst flower patches to optimize nectar influx. The resemblance inspires a honeybee biomimetic algorithm. This paper describes details of the honeybee self-organizing model in terms of information flow and feedback, analyzes the homology between the two problems and derives the resulting biomimetic algorithm for hosting centers. The algorithm is assessed for effectiveness and adaptiveness by comparative testing against benchmark and conventional algorithms. Computational results indicate that the new algorithm is highly adaptive to widely varying external environments and quite competitive against benchmark assessment algorithms. Other swarm intelligence applications are briefly surveyed, and some general speculations are offered regarding their various degrees of success.

Next generation communications satellites: multiple access and network studies

NASA Technical Reports Server (NTRS)

Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.

1982-01-01

Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.

Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

PubMed Central

Lee, Chaewoo

2014-01-01

The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862

Dynamic Capacity Allocation Algorithms for iNET Link Manager

DTIC Science & Technology

2014-05-01

algorithm that can better cope with severe congestion and misbehaving users and traffic flows. We compare the E-LM with the LM baseline algorithm (B-LM...capacity allocation algorithm that can better cope with severe congestion and misbehaving users and traffic flows. We compare the E-LM with the LM

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Analysis and Research on the Optimal Allocation of Regional Water Resources

NASA Astrophysics Data System (ADS)

rui-chao, Xi; yu-jie, Gu

2018-06-01

Starting from the basic concept of optimal allocation of water resources, taking the allocation of water resources in Tianjin as an example, the present situation of water resources in Tianjin is analyzed, and the multi-objective optimal allocation model of water resources is used to optimize the allocation of water resources. We use LINGO to solve the model, get the optimal allocation plan that meets the economic and social benefits, and put forward relevant policies and regulations, so as to provide theoretical which is basis for alleviating and solving the problem of water shortage.

Toward interactive scheduling systems for managing medical resources.

PubMed

Oddi, A; Cesta, A

2000-10-01

Managers of medico-hospital facilities are facing two general problems when allocating resources to activities: (1) to find an agreement between several and contrasting requirements; (2) to manage dynamic and uncertain situations when constraints suddenly change over time due to medical needs. This paper describes the results of a research aimed at applying constraint-based scheduling techniques to the management of medical resources. A mixed-initiative problem solving approach is adopted in which a user and a decision support system interact to incrementally achieve a satisfactory solution to the problem. A running prototype is described called Interactive Scheduler which offers a set of functionalities for a mixed-initiative interaction to cope with the medical resource management. Interactive Scheduler is endowed with a representation schema used for describing the medical environment, a set of algorithms that address the specific problems of the domain, and an innovative interaction module that offers functionalities for the dialogue between the support system and its user. A particular contribution of this work is the explicit representation of constraint violations, and the definition of scheduling algorithms that aim at minimizing the amount of constraint violations in a solution.

A Multiuser Manufacturing Resource Service Composition Method Based on the Bees Algorithm

PubMed Central

Xie, Yongquan; Zhou, Zude; Pham, Duc Truong; Xu, Wenjun; Ji, Chunqian

2015-01-01

In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic Bees Algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems. PMID:26339232

Case-mix groups for VA hospital-based home care.

PubMed

Smith, M E; Baker, C R; Branch, L G; Walls, R C; Grimes, R M; Karklins, J M; Kashner, M; Burrage, R; Parks, A; Rogers, P

1992-01-01

The purpose of this study is to group hospital-based home care (HBHC) patients homogeneously by their characteristics with respect to cost of care to develop alternative case mix methods for management and reimbursement (allocation) purposes. Six Veterans Affairs (VA) HBHC programs in Fiscal Year (FY) 1986 that maximized patient, program, and regional variation were selected, all of which agreed to participate. All HBHC patients active in each program on October 1, 1987, in addition to all new admissions through September 30, 1988 (FY88), comprised the sample of 874 unique patients. Statistical methods include the use of classification and regression trees (CART software: Statistical Software; Lafayette, CA), analysis of variance, and multiple linear regression techniques. The resulting algorithm is a three-factor model that explains 20% of the cost variance (R2 = 20%, with a cross validation R2 of 12%). Similar classifications such as the RUG-II, which is utilized for VA nursing home and intermediate care, the VA outpatient resource allocation model, and the RUG-HHC, utilized in some states for reimbursing home health care in the private sector, explained less of the cost variance and, therefore, are less adequate for VA home care resource allocation.

New Multi-objective Uncertainty-based Algorithm for Water Resource Models' Calibration

NASA Astrophysics Data System (ADS)

Keshavarz, Kasra; Alizadeh, Hossein

2017-04-01

Water resource models are powerful tools to support water management decision making process and are developed to deal with a broad range of issues including land use and climate change impacts analysis, water allocation, systems design and operation, waste load control and allocation, etc. These models are divided into two categories of simulation and optimization models whose calibration has been addressed in the literature where great relevant efforts in recent decades have led to two main categories of auto-calibration methods of uncertainty-based algorithms such as GLUE, MCMC and PEST and optimization-based algorithms including single-objective optimization such as SCE-UA and multi-objective optimization such as MOCOM-UA and MOSCEM-UA. Although algorithms which benefit from capabilities of both types, such as SUFI-2, were rather developed, this paper proposes a new auto-calibration algorithm which is capable of both finding optimal parameters values regarding multiple objectives like optimization-based algorithms and providing interval estimations of parameters like uncertainty-based algorithms. The algorithm is actually developed to improve quality of SUFI-2 results. Based on a single-objective, e.g. NSE and RMSE, SUFI-2 proposes a routine to find the best point and interval estimation of parameters and corresponding prediction intervals (95 PPU) of time series of interest. To assess the goodness of calibration, final results are presented using two uncertainty measures of p-factor quantifying percentage of observations covered by 95PPU and r-factor quantifying degree of uncertainty, and the analyst has to select the point and interval estimation of parameters which are actually non-dominated regarding both of the uncertainty measures. Based on the described properties of SUFI-2, two important questions are raised, answering of which are our research motivation: Given that in SUFI-2, final selection is based on the two measures or objectives and on the other hand, knowing that there is no multi-objective optimization mechanism in SUFI-2, are the final estimations Pareto-optimal? Can systematic methods be applied to select the final estimations? Dealing with these questions, a new auto-calibration algorithm was proposed where the uncertainty measures were considered as two objectives to find non-dominated interval estimations of parameters by means of coupling Monte Carlo simulation and Multi-Objective Particle Swarm Optimization. Both the proposed algorithm and SUFI-2 were applied to calibrate parameters of water resources planning model of Helleh river basin, Iran. The model is a comprehensive water quantity-quality model developed in the previous researches using WEAP software in order to analyze the impacts of different water resources management strategies including dam construction, increasing cultivation area, utilization of more efficient irrigation technologies, changing crop pattern, etc. Comparing the Pareto frontier resulted from the proposed auto-calibration algorithm with SUFI-2 results, it was revealed that the new algorithm leads to a better and also continuous Pareto frontier, even though it is more computationally expensive. Finally, Nash and Kalai-Smorodinsky bargaining methods were used to choose compromised interval estimation regarding Pareto frontier.

Improving hospital bed occupancy and resource utilization through queuing modeling and evolutionary computation.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2015-02-01

Scarce healthcare resources require carefully made policies ensuring optimal bed allocation, quality healthcare service, and adequate financial support. This paper proposes a complex analysis of the resource allocation in a hospital department by integrating in the same framework a queuing system, a compartmental model, and an evolutionary-based optimization. The queuing system shapes the flow of patients through the hospital, the compartmental model offers a feasible structure of the hospital department in accordance to the queuing characteristics, and the evolutionary paradigm provides the means to optimize the bed-occupancy management and the resource utilization using a genetic algorithm approach. The paper also focuses on a "What-if analysis" providing a flexible tool to explore the effects on the outcomes of the queuing system and resource utilization through systematic changes in the input parameters. The methodology was illustrated using a simulation based on real data collected from a geriatric department of a hospital from London, UK. In addition, the paper explores the possibility of adapting the methodology to different medical departments (surgery, stroke, and mental illness). Moreover, the paper also focuses on the practical use of the model from the healthcare point of view, by presenting a simulated application. Copyright © 2014 Elsevier Inc. All rights reserved.

Children’s Recognition of Fairness and Others’ Welfare in a Resource Allocation Task: Age Related Changes

PubMed Central

Rizzo, Michael T.; Elenbaas, Laura; Cooley, Shelby; Killen, Melanie

2016-01-01

The present study investigated age-related changes regarding children’s (N = 136) conceptions of fairness and others’ welfare in a merit-based resource allocation paradigm. To test whether children at 3- to 5-years-old and 6- to 8-years-old took others’ welfare into account when dividing resources, in addition to merit and equality concerns, children were asked to allocate, judge, and reason about allocations of necessary (needed to avoid harm) and luxury (enjoyable to have) resources to a hardworking and a lazy character. While 3- to 5-year-olds did not differentiate between distributing luxury and necessary resources, 6- to 8-year-olds allocated luxury resources more meritoriously than necessary resources. Further, children based their allocations of necessary resources on concerns for others’ welfare, rather than merit, even when one character was described as working harder. The findings revealed that, with age, children incorporated the concerns for others’ welfare and merit into their conceptions of fairness in a resource allocation context, and prioritized these concerns differently depending on whether they were allocating luxury or necessary resources. Further, with age, children weighed multiple moral concerns including equality, merit, and others’ welfare, when determining the fair allocation of resources. PMID:27455189

The ontogeny of postmaturation resource allocation in turtles.

PubMed

Bowden, R M; Paitz, Ryan T; Janzen, Fredric J

2011-01-01

Resource-allocation decisions vary with life-history strategy, and growing evidence suggests that long-lived endothermic vertebrates direct resources toward growth and self-maintenance when young, increasing allocation toward reproductive effort over time. Few studies have tracked the ontogeny of resource allocation (energy, steroid hormones, etc.) in long-lived ectothermic vertebrates, limiting our understanding of the generality of life-history strategies among vertebrates. We investigated how reproductively mature female painted turtles (Chrysemys picta) from two distinct age classes allocated resources over a 4-yr period and whether resource-allocation patterns varied with nesting experience. We examined age-related variation in body size, egg mass, reproductive frequency, and yolk steroids and report that younger females were smaller and allocated fewer resources to reproduction than did older females. Testosterone levels were higher in eggs from younger females, whereas eggs from second (seasonal) clutches contained higher concentrations of progesterone and estradiol. These allocation patterns resulted in older, larger females laying larger eggs and producing second clutches more frequently than their younger counterparts. We conclude that resource-allocation patterns do vary with age in a long-lived ectotherm.

Optimized maritime emergency resource allocation under dynamic demand.

PubMed

Zhang, Wenfen; Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

Optimized maritime emergency resource allocation under dynamic demand

PubMed Central

Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand. PMID:29240792

[Equity of Health Resources Allocation in Minority Regions of Sichuan Province].

PubMed

Chen, Nan; Tang, Wen; Liang, Zhi; Zou, Bo; Li, Xiao-song

2016-03-01

To determine equity of health resources allocation in minority regions of Sichuan province from 2009 to 2013. Health resources distribution equity among populations and across geographic catchments were measured using coefficients of Inter-Individual differences and Individual-Mean differences. Health resources, especially human resources, in minority regions increased slowly over the years. Poorer allocation equity was found in nursing resources compared with doctors and hospital beds. Better distribution equity was found among populations than across geographic catchments. High levels of equity in resource distributions among populations and across geographic catchments were found in Aba. In Liangshan, more equitable distributions were found in doctors and hospital beds compared with nurses. The rest of minority regions had poor absolute allocation equity in doctors and hospital beds among populations. Appropriate allocation of health resources can promote health development. Health resources allocation in minority regions of Sichuan province is unreasonable. The government and relevant departments should take actions to optimize health resources allocations.

Bayesian dose selection design for a binary outcome using restricted response adaptive randomization.

PubMed

Meinzer, Caitlyn; Martin, Renee; Suarez, Jose I

2017-09-08

In phase II trials, the most efficacious dose is usually not known. Moreover, given limited resources, it is difficult to robustly identify a dose while also testing for a signal of efficacy that would support a phase III trial. Recent designs have sought to be more efficient by exploring multiple doses through the use of adaptive strategies. However, the added flexibility may potentially increase the risk of making incorrect assumptions and reduce the total amount of information available across the dose range as a function of imbalanced sample size. To balance these challenges, a novel placebo-controlled design is presented in which a restricted Bayesian response adaptive randomization (RAR) is used to allocate a majority of subjects to the optimal dose of active drug, defined as the dose with the lowest probability of poor outcome. However, the allocation between subjects who receive active drug or placebo is held constant to retain the maximum possible power for a hypothesis test of overall efficacy comparing the optimal dose to placebo. The design properties and optimization of the design are presented in the context of a phase II trial for subarachnoid hemorrhage. For a fixed total sample size, a trade-off exists between the ability to select the optimal dose and the probability of rejecting the null hypothesis. This relationship is modified by the allocation ratio between active and control subjects, the choice of RAR algorithm, and the number of subjects allocated to an initial fixed allocation period. While a responsive RAR algorithm improves the ability to select the correct dose, there is an increased risk of assigning more subjects to a worse arm as a function of ephemeral trends in the data. A subarachnoid treatment trial is used to illustrate how this design can be customized for specific objectives and available data. Bayesian adaptive designs are a flexible approach to addressing multiple questions surrounding the optimal dose for treatment efficacy within the context of limited resources. While the design is general enough to apply to many situations, future work is needed to address interim analyses and the incorporation of models for dose response.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Cancer Diagnosis Epigenomics Scientific Workflow Scheduling in the Cloud Computing Environment Using an Improved PSO Algorithm

PubMed

N, Sadhasivam; R, Balamurugan; M, Pandi

2018-01-27

Objective: Epigenetic modifications involving DNA methylation and histone statud are responsible for the stable maintenance of cellular phenotypes. Abnormalities may be causally involved in cancer development and therefore could have diagnostic potential. The field of epigenomics refers to all epigenetic modifications implicated in control of gene expression, with a focus on better understanding of human biology in both normal and pathological states. Epigenomics scientific workflow is essentially a data processing pipeline to automate the execution of various genome sequencing operations or tasks. Cloud platform is a popular computing platform for deploying large scale epigenomics scientific workflow. Its dynamic environment provides various resources to scientific users on a pay-per-use billing model. Scheduling epigenomics scientific workflow tasks is a complicated problem in cloud platform. We here focused on application of an improved particle swam optimization (IPSO) algorithm for this purpose. Methods: The IPSO algorithm was applied to find suitable resources and allocate epigenomics tasks so that the total cost was minimized for detection of epigenetic abnormalities of potential application for cancer diagnosis. Result: The results showed that IPSO based task to resource mapping reduced total cost by 6.83 percent as compared to the traditional PSO algorithm. Conclusion: The results for various cancer diagnosis tasks showed that IPSO based task to resource mapping can achieve better costs when compared to PSO based mapping for epigenomics scientific application workflow. Creative Commons Attribution License

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

ACARA user's manual

NASA Technical Reports Server (NTRS)

Stalnaker, Dale K.

1993-01-01

ACARA (Availability, Cost, and Resource Allocation) is a computer program which analyzes system availability, lifecycle cost (LCC), and resupply scheduling using Monte Carlo analysis to simulate component failure and replacement. This manual was written to: (1) explain how to prepare and enter input data for use in ACARA; (2) explain the user interface, menus, input screens, and input tables; (3) explain the algorithms used in the program; and (4) explain each table and chart in the output.

Configuration of Wireless Cooperative/Sensor Networks

DTIC Science & Technology

2008-05-25

WSN), the advantages of cooperation can be further exploited by optimally allocating the energy and bandwidth resources among users based on the... consumption and extend system lifetime [Sin98]. The implementation of a minimum energy routing protocol is discussed in [Dos02a, Dos02b]. An online...power consumption in the network given the required SER at the destination. For example, with source power Ps=20dB, the EP algorithm requires one relay

Fort Benning Land-Use Planning and Management Study

DTIC Science & Technology

1990-04-01

process is three-tiered: (a) an initial phase that results in preliminary allocations for natural resources, (b) a second phase that focuses on...allocations of military training requirements, and (c) a final phase that resolves conflicts between the military and natural resource requirements and...assigns final allocations. 34. Initial phase : Natural resource allocations. The first step in this phase was to make allocations among natural resource

The past, present and future of HIV, AIDS and resource allocation

PubMed Central

2009-01-01

Background How should HIV and AIDS resources be allocated to achieve the greatest possible impact? This paper begins with a theoretical discussion of this issue, describing the key elements of an "evidence-based allocation strategy". While it is noted that the quality of epidemiological and economic data remains inadequate to define such an optimal strategy, there do exist tools and research which can lead countries in a way that they can make allocation decisions. Furthermore, there are clear indications that most countries are not allocating their HIV and AIDS resources in a way which is likely to achieve the greatest possible impact. For example, it is noted that neighboring countries, even when they have a similar prevalence of HIV, nonetheless often allocate their resources in radically different ways. These differing allocation patterns appear to be attributable to a number of different issues, including a lack of data, contradictory results in existing data, a need for overemphasizing a multisectoral response, a lack of political will, a general inefficiency in the use of resources when they do get allocated, poor planning and a lack of control over the way resources get allocated. Methods There are a number of tools currently available which can improve the resource-allocation process. Tools such as the Resource Needs Model (RNM) can provide policymakers with a clearer idea of resource requirements, whereas other tools such as Goals and the Allocation by Cost-Effectiveness (ABCE) models can provide countries with a clearer vision of how they might reallocate funds. Results Examples from nine different countries provide information about how policymakers are trying to make their resource-allocation strategies more "evidence based". By identifying the challenges and successes of these nine countries in making more informed allocation decisions, it is hoped that future resource-allocation decisions for all countries can be improved. Conclusion We discuss the future of resource allocation, noting the types of additional data which will be required and the improvements in existing tools which could be made. PMID:19922688

System Resource Allocations | High-Performance Computing | NREL

Science.gov Websites

Allocations System Resource Allocations To use NREL's high-performance computing (HPC) resources : Compute hours on NREL HPC Systems including Peregrine and Eagle Storage space (in Terabytes) on Peregrine , Eagle and Gyrfalcon. Allocations are principally done in response to an annual call for allocation

An enhanced DWBA algorithm in hybrid WDM/TDM EPON networks with heterogeneous propagation delays

NASA Astrophysics Data System (ADS)

Li, Chengjun; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2011-12-01

An enhanced dynamic wavelength and bandwidth allocation (DWBA) algorithm in hybrid WDM/TDM PON is proposed and experimentally demonstrated. In addition to the fairness of bandwidth allocation, this algorithm also considers the varying propagation delays between ONUs and OLT. The simulation based on MATLAB indicates that the improved algorithm has a better performance compared with some other algorithms.

Dynamic Staffing and Rescheduling in Software Project Management: A Hybrid Approach.

PubMed

Ge, Yujia; Xu, Bin

2016-01-01

Resource allocation could be influenced by various dynamic elements, such as the skills of engineers and the growth of skills, which requires managers to find an effective and efficient tool to support their staffing decision-making processes. Rescheduling happens commonly and frequently during the project execution. Control options have to be made when new resources are added or tasks are changed. In this paper we propose a software project staffing model considering dynamic elements of staff productivity with a Genetic Algorithm (GA) and Hill Climbing (HC) based optimizer. Since a newly generated reschedule dramatically different from the initial schedule could cause an obvious shifting cost increase, our rescheduling strategies consider both efficiency and stability. The results of real world case studies and extensive simulation experiments show that our proposed method is effective and could achieve comparable performance to other heuristic algorithms in most cases.

Dynamic Staffing and Rescheduling in Software Project Management: A Hybrid Approach

PubMed Central

Ge, Yujia; Xu, Bin

2016-01-01

Resource allocation could be influenced by various dynamic elements, such as the skills of engineers and the growth of skills, which requires managers to find an effective and efficient tool to support their staffing decision-making processes. Rescheduling happens commonly and frequently during the project execution. Control options have to be made when new resources are added or tasks are changed. In this paper we propose a software project staffing model considering dynamic elements of staff productivity with a Genetic Algorithm (GA) and Hill Climbing (HC) based optimizer. Since a newly generated reschedule dramatically different from the initial schedule could cause an obvious shifting cost increase, our rescheduling strategies consider both efficiency and stability. The results of real world case studies and extensive simulation experiments show that our proposed method is effective and could achieve comparable performance to other heuristic algorithms in most cases. PMID:27285420

A sustainable genetic algorithm for satellite resource allocation

NASA Technical Reports Server (NTRS)

Abbott, R. J.; Campbell, M. L.; Krenz, W. C.

1995-01-01

A hybrid genetic algorithm is used to schedule tasks for 8 satellites, which can be modelled as a robot whose task is to retrieve objects from a two dimensional field. The objective is to find a schedule that maximizes the value of objects retrieved. Typical of the real-world tasks to which this corresponds is the scheduling of ground contacts for a communications satellite. An important feature of our application is that the amount of time available for running the scheduler is not necessarily known in advance. This requires that the scheduler produce reasonably good results after a short period but that it also continue to improve its results if allowed to run for a longer period. We satisfy this requirement by developing what we call a sustainable genetic algorithm.

Optimizing conjunctive use of surface water and groundwater resources with stochastic dynamic programming

NASA Astrophysics Data System (ADS)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter

2014-05-01

Optimal management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to optimize conjunctive use of scarce surface water and groundwater resources under uncertainty is presented. A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the optimal management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate and future costs for given surface water reservoir and groundwater aquifer end storages. The immediate cost is found by solving a simple linear allocation sub-problem, and the future costs are assessed by interpolation in the total cost matrix from the following time step. Total costs for all stages, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two-reservoir system the future cost function would have to be represented by a set of planes, and strict convexity in both the surface water and groundwater dimension cannot be maintained. The optimization framework based on the GA is still computationally feasible and represents a clean and customizable method. The method has been applied to the Ziya River basin, China. The basin is located on the North China Plain and is subject to severe water scarcity, which includes surface water droughts and groundwater over-pumping. The head-dependent groundwater pumping costs will enable assessment of the long-term effects of increased electricity prices on the groundwater pumping. The coupled optimization framework is used to assess realistic alternative development scenarios for the basin. In particular the potential for using electricity pricing policies to reach sustainable groundwater pumping is investigated.

Equity in health care in Namibia: developing a needs-based resource allocation formula using principal components analysis

PubMed Central

Zere, Eyob; Mandlhate, Custodia; Mbeeli, Thomas; Shangula, Kalumbi; Mutirua, Kauto; Kapenambili, William

2007-01-01

Background The pace of redressing inequities in the distribution of scarce health care resources in Namibia has been slow. This is due primarily to adherence to the historical incrementalist type of budgeting that has been used to allocate resources. Those regions with high levels of deprivation and relatively greater need for health care resources have been getting less than their fair share. To rectify this situation, which was inherited from the apartheid system, there is a need to develop a needs-based resource allocation mechanism. Methods Principal components analysis was employed to compute asset indices from asset based and health-related variables, using data from the Namibia demographic and health survey of 2000. The asset indices then formed the basis of proposals for regional weights for establishing a needs-based resource allocation formula. Results Comparing the current allocations of public sector health car resources with estimates using a needs based formula showed that regions with higher levels of need currently receive fewer resources than do regions with lower need. Conclusion To address the prevailing inequities in resource allocation, the Ministry of Health and Social Services should abandon the historical incrementalist method of budgeting/resource allocation and adopt a more appropriate allocation mechanism that incorporates measures of need for health care. PMID:17391533

Equity in health care in Namibia: developing a needs-based resource allocation formula using principal components analysis.

PubMed

Zere, Eyob; Mandlhate, Custodia; Mbeeli, Thomas; Shangula, Kalumbi; Mutirua, Kauto; Kapenambili, William

2007-03-29

The pace of redressing inequities in the distribution of scarce health care resources in Namibia has been slow. This is due primarily to adherence to the historical incrementalist type of budgeting that has been used to allocate resources. Those regions with high levels of deprivation and relatively greater need for health care resources have been getting less than their fair share. To rectify this situation, which was inherited from the apartheid system, there is a need to develop a needs-based resource allocation mechanism. Principal components analysis was employed to compute asset indices from asset based and health-related variables, using data from the Namibia demographic and health survey of 2000. The asset indices then formed the basis of proposals for regional weights for establishing a needs-based resource allocation formula. Comparing the current allocations of public sector health car resources with estimates using a needs based formula showed that regions with higher levels of need currently receive fewer resources than do regions with lower need. To address the prevailing inequities in resource allocation, the Ministry of Health and Social Services should abandon the historical incrementalist method of budgeting/resource allocation and adopt a more appropriate allocation mechanism that incorporates measures of need for health care.

Dynamic equilibrium strategy for drought emergency temporary water transfer and allocation management

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Ma, Ning; Lv, Chengwei

2016-08-01

Efficient water transfer and allocation are critical for disaster mitigation in drought emergencies. This is especially important when the different interests of the multiple decision makers and the fluctuating water resource supply and demand simultaneously cause space and time conflicts. To achieve more effective and efficient water transfers and allocations, this paper proposes a novel optimization method with an integrated bi-level structure and a dynamic strategy, in which the bi-level structure works to deal with space dimension conflicts in drought emergencies, and the dynamic strategy is used to deal with time dimension conflicts. Combining these two optimization methods, however, makes calculation complex, so an integrated interactive fuzzy program and a PSO-POA are combined to develop a hybrid-heuristic algorithm. The successful application of the proposed model in a real world case region demonstrates its practicality and efficiency. Dynamic cooperation between multiple reservoirs under the coordination of a global regulator reflects the model's efficiency and effectiveness in drought emergency water transfer and allocation, especially in a fluctuating environment. On this basis, some corresponding management recommendations are proposed to improve practical operations.

Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors

NASA Astrophysics Data System (ADS)

Habibi Davijani, M.; Banihabib, M. E.; Nadjafzadeh Anvar, A.; Hashemi, S. R.

2016-02-01

In many discussions, work force is mentioned as the most important factor of production. Principally, work force is a factor which can compensate for the physical and material limitations and shortcomings of other factors to a large extent which can help increase the production level. On the other hand, employment is considered as an effective factor in social issues. The goal of the present research is the allocation of water resources so as to maximize the number of jobs created in the industry and agriculture sectors. An objective that has attracted the attention of policy makers involved in water supply and distribution is the maximization of the interests of beneficiaries and consumers in case of certain policies adopted. The present model applies the particle swarm optimization (PSO) algorithm in order to determine the optimum amount of water allocated to each water-demanding sector, area under cultivation, agricultural production, employment in the agriculture sector, industrial production and employment in the industry sector. Based on the results obtained from this research, by optimally allocating water resources in the central desert region of Iran, 1096 jobs can be created in the industry and agriculture sectors, which constitutes an improvement of about 13% relative to the previous situation (non-optimal water utilization). It is also worth mentioning that by optimizing the employment factor as a social parameter, the other areas such as the economic sector are influenced as well. For example, in this investigation, the resulting economic benefits (incomes) have improved from 73 billion Rials at baseline employment figures to 112 billion Rials in the case of optimized employment condition. Therefore, it is necessary to change the inter-sector and intra-sector water allocation models in this region, because this change not only leads to more jobs in this area, but also causes an improvement in the region's economic conditions.

A review of alternative approaches to healthcare resource allocation.

PubMed

Petrou, S; Wolstenholme, J

2000-07-01

The resources available for healthcare are limited compared with demand, if not need, and all healthcare systems, regardless of their financing and organisation, employ mechanisms to ration or prioritise finite healthcare resources. This paper reviews alternative approaches that can be used to allocate healthcare resources. It discusses the problems encountered when allocating healthcare resources according to free market principles. It then proceeds to discuss the advantages and disadvantages of alternative resource allocation approaches that can be applied to public health systems. These include: (i) approaches based on the concept of meeting the needs of the population to maximising its capacity to benefit from interventions; (ii) economic approaches that identify the most efficient allocation of resources with the view of maximising health benefits or other measures of social welfare; (iii) approaches that seek to ration healthcare by age; and (iv) approaches that resolve resource allocation disputes through debate and bargaining. At present, there appears to be no consensus about the relative importance of the potentially conflicting principles that can be used to guide resource allocation decisions. It is concluded that whatever shape tomorrow's health service takes, the requirement to make equitable and efficient use of finite healthcare resources will remain.

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

National equity of health resource allocation in China: data from 2009 to 2013.

PubMed

Liu, Wen; Liu, Ying; Twum, Peter; Li, Shixue

2016-04-19

The inequitable allocation of health resources is a worldwide problem, and it is also one of the obstacles facing for health services utilization in China. A new round of health care reform which contains the important aspect of improving the equity in health resource allocation was released by Chinese government in 2009. The aim of this study is to understand the changes of equity in health resource allocation from 2009 to 2013, and make a further inquiry of the main factors which influence the equity conditions in China. Data resources are the China Health Statistics Yearbook (2014) and the China Statistical Yearbook (2014). Four indicators were chosen to measure the trends in equity of health resource allocation. Data were disaggregated by three geographical regions: west, central, and east. Theil index was used to calculate the degree of unfairness. The total amount of health care resources in China had been increasing in recent years. However, the per 10, 000 km(2) number of health resources showed a huge gap in different regions, and per 10, 000 capita health resources ownership showed a relatively small disparities at the same time. The index of health resources showed an overall downward trend, in which health financial investment the most unfair from 2009 to 2012 and the number of health institutions the most unfair in 2013. The equity of health resources allocation in eastern regions was the worst except for the aspect of health technical personnel allocation. The regional contribution rates were lower than that of the inter-regional contribution rates which were all beyond 60 %. The equity of health resource allocation improved gradually from 2009 to 2013. However, the internal differences within the eastern region still have a huge impact on the overall equity in health resource allocation. The tough issues of inequitable in health resource allocation should be resolved by comprehensive measures from a multidisciplinary perspective.

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Youngblood, John N.; Saha, Aindam

1987-01-01

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Computer architecture for efficient algorithmic executions in real-time systems: new technology for avionics systems and advanced space vehicles

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

Carroll, C.C.; Youngblood, J.N.; Saha, A.

1987-12-01

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processingmore » elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.« less

Resource Allocation Based on Evaluation of Research.

ERIC Educational Resources Information Center

Fransson, Rune

1985-01-01

At Sweden's Karolinska Institute, a resource allocation model for medical research in use since 1970 allows the research activity of the different departments to affect resource allocation direclty. (MSE)

A group-based tasks allocation algorithm for the optimization of long leave opportunities in academic departments

NASA Astrophysics Data System (ADS)

Eyono Obono, S. D.; Basak, Sujit Kumar

2011-12-01

The general formulation of the assignment problem consists in the optimal allocation of a given set of tasks to a workforce. This problem is covered by existing literature for different domains such as distributed databases, distributed systems, transportation, packets radio networks, IT outsourcing, and teaching allocation. This paper presents a new version of the assignment problem for the allocation of academic tasks to staff members in departments with long leave opportunities. It presents the description of a workload allocation scheme and its algorithm, for the allocation of an equitable number of tasks in academic departments where long leaves are necessary.

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

75 FR 27850 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-18

... Change, as Modified by Amendment No. 1 Thereto, Related to the Hybrid Matching Algorithms May 12, 2010... allocation algorithms to choose from when executing incoming electronic orders. The menu format allows the Exchange to utilize different allocation algorithms on a class-by-class basis. The menu includes, among...

Fog computing job scheduling optimization based on bees swarm

NASA Astrophysics Data System (ADS)

Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

2018-04-01

Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

Multicast backup reprovisioning problem for Hamiltonian cycle-based protection on WDM networks

NASA Astrophysics Data System (ADS)

Din, Der-Rong; Huang, Jen-Shen

2014-03-01

As networks grow in size and complexity, the chance and the impact of failures increase dramatically. The pre-allocated backup resources cannot provide 100% protection guarantee when continuous failures occur in a network. In this paper, the multicast backup re-provisioning problem (MBRP) for Hamiltonian cycle (HC)-based protection on WDM networks for the link-failure case is studied. We focus on how to recover the protecting capabilities of Hamiltonian cycle against the subsequent link-failures on WDM networks for multicast transmissions, after recovering the multicast trees affected by the previous link-failure. Since this problem is a hard problem, an algorithm, which consists of several heuristics and a genetic algorithm (GA), is proposed to solve it. The simulation results of the proposed method are also given. Experimental results indicate that the proposed algorithm can solve this problem efficiently.

Examination of Resource Allocation in Education: Connecting Spending to Student Performance. Research Report.

ERIC Educational Resources Information Center

Pan, Diane; Rudo, Zena H.; Schneider, Cynthia L.; Smith-Hansen, Lotte

This document reports on a study on the relationship between resources and student performance. The study examined district-level patterns of resource allocation, district and school resource practices implemented to improve student performance, and barriers and challenges to efficient resource allocation faced by districts and schools. The study…

A data-driven allocation tool for in-kind resources distributed by a state health department.

PubMed

Peterson, Cora; Kegler, Scott R; Parker, Wende R; Sullivan, David

2016-10-02

The objective of this study was to leverage a state health department's operational data to allocate in-kind resources (children's car seats) to counties, with the proposition that need-based allocation could ultimately improve public health outcomes. This study used a retrospective analysis of administrative data on car seats distributed to counties statewide by the Georgia Department of Public Health and development of a need-based allocation tool (presented as interactive supplemental digital content, adaptable to other types of in-kind public health resources) that relies on current county-level injury and sociodemographic data. Car seat allocation using public health data and a need-based formula resulted in substantially different recommended allocations to individual counties compared to historic distribution. Results indicate that making an in-kind public health resource like car seats universally available results in a less equitable distribution of that resource compared to deliberate allocation according to public health need. Public health agencies can use local data to allocate in-kind resources consistent with health objectives; that is, in a manner offering the greatest potential health impact. Future analysis can determine whether the change to a more equitable allocation of resources is also more efficient, resulting in measurably improved public health outcomes.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

A model of interaction between anticorruption authority and corruption groups

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

Neverova, Elena G.; Malafeyef, Oleg A.

The paper provides a model of interaction between anticorruption unit and corruption groups. The main policy functions of the anticorruption unit involve reducing corrupt practices in some entities through an optimal approach to resource allocation and effective anticorruption policy. We develop a model based on Markov decision-making process and use Howard’s policy-improvement algorithm for solving an optimal decision strategy. We examine the assumption that corruption groups retaliate against the anticorruption authority to protect themselves. This model was implemented through stochastic game.

Resource Allocation and Cross Layer Control in Wireless Networks

DTIC Science & Technology

2006-08-25

arrival rates lies within the capacity region of the network. The notion of controlling the system to maximize its stability region and the following...optimization problem (4.5) that must be solved at the beginning of 48 Dynamic Control for Network Stability each time slot requires in general knowledge...Dynamic Control for Network Stability ~ (c) ab (t) those of any other feasible algorithm, then for any time t 0; X ic U (c) i (t) "X b ~ (c) ab (t) X

Nation-Building Modeling and Resource Allocation Via Dynamic Programming

DTIC Science & Technology

2014-09-01

Figure 2. RAND Study Models[59:98,115] (WMA) and used both the k-Nearest Neighbor ( KNN ) and Nearest Centroid (NC) algorithms to classify future features...The study found that KNN performed bet- ter than NC with 85% or greater accuracy in all test cases. The methodology was adopted for use under the...analysis feature of the model. 3.7.1 The No Surge Alternative. On the 10th of January 2007, President George W. Bush delivered a speech to the American

Automated electric power management and control for Space Station Freedom

NASA Technical Reports Server (NTRS)

Dolce, James L.; Mellor, Pamela A.; Kish, James A.

1990-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. It strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. An integrated approach to the power system command and control problem is defined and used to direct technology development in: diagnosis, security monitoring and analysis, battery management, and cooperative problem-solving for resource allocation. The prototype automated power system is developed using simulations and test-beds.

Theory of Mind is Related to Children’s Resource Allocations in Gender Stereotypic Contexts

PubMed Central

Rizzo, Michael T.; Killen, Melanie

2017-01-01

The present study investigated the relations between 4- to 6-year-old children’s (N = 67) gender stereotypes, resource allocations, and mental state knowledge in gender stereotypic contexts. Participants were told vignettes about female and male characters completing gender-stereotyped activities (making dolls or trucks). Children held stereotypic expectations regarding doll- and truck-making abilities, and these expectations predicted the degree of bias in their allocations of resources to the characters. Critically, children’s performance on a ToM scale (Diverse Desires, Contents False-Belief, Belief-Emotion) was significantly related to their allocations of resources to individuals whose effort did not fit existing gender stereotypes (e.g., a boy who was good at making dolls). With increasing ToM competence, children allocated resources based on merit (even when the character’s effort did not fit existing gender stereotypes) rather than based on stereotypes. The present results provide novel information regarding the emergence of gender stereotypes about abilities, the influence of stereotypes on children’s resource allocations, and the role of ToM in children’s ability to challenge gender stereotypes when allocating resources. PMID:29083217

A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling

NASA Astrophysics Data System (ADS)

Joa, Eunhyek; Park, Kwanwoo; Koh, Youngil; Yi, Kyongsu; Kim, Kilsoo

2018-04-01

This paper presents a tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel braking for enhanced performance from moderate driving to limit handling. The proposed algorithm adopted hierarchical structure: supervisor - desired motion tracking controller - optimisation-based control allocation. In the supervisor, by considering transient cornering characteristics, desired vehicle motion is calculated. In the desired motion tracking controller, in order to track desired vehicle motion, virtual control input is determined in the manner of sliding mode control. In the control allocation, virtual control input is allocated to minimise cost function. The cost function consists of two major parts. First part is a slip-based tyre friction utilisation quantification, which does not need a tyre force estimation. Second part is an allocation guideline, which guides optimally allocated inputs to predefined solution. The proposed algorithm has been investigated via simulation from moderate driving to limit handling scenario. Compared to Base and direct yaw moment control system, the proposed algorithm can effectively reduce tyre dissipation energy in the moderate driving situation. Moreover, the proposed algorithm enhances limit handling performance compared to Base and direct yaw moment control system. In addition to comparison with Base and direct yaw moment control, comparison the proposed algorithm with the control algorithm based on the known tyre force information has been conducted. The results show that the performance of the proposed algorithm is similar with that of the control algorithm with the known tyre force information.

Complex Genetic Effects on Early Vegetative Development Shape Resource Allocation Differences Between Arabidopsis lyrata Populations

PubMed Central

Remington, David L.; Leinonen, Päivi H.; Leppälä, Johanna; Savolainen, Outi

2013-01-01

Costs of reproduction due to resource allocation trade-offs have long been recognized as key forces in life history evolution, but little is known about their functional or genetic basis. Arabidopsis lyrata, a perennial relative of the annual model plant A. thaliana with a wide climatic distribution, has populations that are strongly diverged in resource allocation. In this study, we evaluated the genetic and functional basis for variation in resource allocation in a reciprocal transplant experiment, using four A. lyrata populations and F2 progeny from a cross between North Carolina (NC) and Norway parents, which had the most divergent resource allocation patterns. Local alleles at quantitative trait loci (QTL) at a North Carolina field site increased reproductive output while reducing vegetative growth. These QTL had little overlap with flowering date QTL. Structural equation models incorporating QTL genotypes and traits indicated that resource allocation differences result primarily from QTL effects on early vegetative growth patterns, with cascading effects on later vegetative and reproductive development. At a Norway field site, North Carolina alleles at some of the same QTL regions reduced survival and reproductive output components, but these effects were not associated with resource allocation trade-offs in the Norway environment. Our results indicate that resource allocation in perennial plants may involve important adaptive mechanisms largely independent of flowering time. Moreover, the contributions of resource allocation QTL to local adaptation appear to result from their effects on developmental timing and its interaction with environmental constraints, and not from simple models of reproductive costs. PMID:23979581

S4HARA: System for HIV/AIDS resource allocation.

PubMed

Lasry, Arielle; Carter, Michael W; Zaric, Gregory S

2008-03-26

HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA) that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation. S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa. The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease. Condom uptake at the clinic should be increased by changing the condom distribution policy from a pull system to a push system. NGOs and donors promoting antiretroviral programs at the clinic should be sensitized to the results of the model and urged to invest in wellness programs aimed at the prevention and treatment of opportunistic infections. S4HARA differentiates itself from other decision support tools by providing rational HIV/AIDS resource allocation capabilities as well as consideration of the realities facing authorities in their decision-making process.

76 FR 59754 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-27

... priority allocation algorithm for the SPXPM option class,\\5\\ subject to certain conditions. \\5\\ SPXPM is... algorithm in effect for the class, subject to various conditions set forth in subparagraphs (b)(3)(A... permit the allocation algorithm in effect for AIM in the SPXPM option class to be the price-time priority...

75 FR 81704 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-28

... algorithm \\5\\ for HOSS and to make related changes to Interpretation and Policy .03. Currently, there are... applicable allocation algorithm for the HOSS and modified HOSS rotation procedures. Paragraph (c)(iv) of the... allocation algorithm in effect for the option class pursuant to Rule 6.45A or 6.45B), then to limit orders...

Resource Allocation in Public Research Universities

ERIC Educational Resources Information Center

Santos, Jose L.

2007-01-01

The purpose of this study was to conduct an econometric analysis of internal resource allocation. Two theories are used for this study of resource allocation in public research universities, and these are: (1) Theory of the Firm; and (2) Resource Dependence Theory. This study used the American Association of Universities Data Exchange (AAUDE)…

Biomass Allocation of Stoloniferous and Rhizomatous Plant in Response to Resource Availability: A Phylogenetic Meta-Analysis

PubMed Central

Xie, Xiu-Fang; Hu, Yu-Kun; Pan, Xu; Liu, Feng-Hong; Song, Yao-Bin; Dong, Ming

2016-01-01

Resource allocation to different functions is central in life-history theory. Plasticity of functional traits allows clonal plants to regulate their resource allocation to meet changing environments. In this study, biomass allocation traits of clonal plants were categorized into absolute biomass for vegetative growth vs. for reproduction, and their relative ratios based on a data set including 115 species and derived from 139 published literatures. We examined general pattern of biomass allocation of clonal plants in response to availabilities of resource (e.g., light, nutrients, and water) using phylogenetic meta-analysis. We also tested whether the pattern differed among clonal organ types (stolon vs. rhizome). Overall, we found that stoloniferous plants were more sensitive to light intensity than rhizomatous plants, preferentially allocating biomass to vegetative growth, aboveground part and clonal reproduction under shaded conditions. Under nutrient- and water-poor condition, rhizomatous plants were constrained more by ontogeny than by resource availability, preferentially allocating biomass to belowground part. Biomass allocation between belowground and aboveground part of clonal plants generally supported the optimal allocation theory. No general pattern of trade-off was found between growth and reproduction, and neither between sexual and clonal reproduction. Using phylogenetic meta-analysis can avoid possible confounding effects of phylogeny on the results. Our results shown the optimal allocation theory explained a general trend, which the clonal plants are able to plastically regulate their biomass allocation, to cope with changing resource availability, at least in stoloniferous and rhizomatous plants. PMID:27200071

Children's Evaluations of Resource Allocation in the Context of Group Norms

ERIC Educational Resources Information Center

Cooley, Shelby; Killen, Melanie

2015-01-01

This study investigated children's evaluations of peer group members who deviated from group norms about equal and unequal allocation of resources. Children, ages 3.5 to 4 years and 5 to 6 years (N = 73), were asked to evaluate a peer group member who deviated from 1 of 2 group allocation norms: (a) equal allocation of resources, or (b) unequal…

An integrated and dynamic optimisation model for the multi-level emergency logistics network in anti-bioterrorism system

NASA Astrophysics Data System (ADS)

Liu, Ming; Zhao, Lindu

2012-08-01

Demand for emergency resources is usually uncertain and varies quickly in anti-bioterrorism system. Besides, emergency resources which had been allocated to the epidemic areas in the early rescue cycle will affect the demand later. In this article, an integrated and dynamic optimisation model with time-varying demand based on the epidemic diffusion rule is constructed. The heuristic algorithm coupled with the MATLAB mathematical programming solver is adopted to solve the optimisation model. In what follows, the application of the optimisation model as well as a short sensitivity analysis of the key parameters in the time-varying demand forecast model is presented. The results show that both the model and the solution algorithm are useful in practice, and both objectives of inventory level and emergency rescue cost can be controlled effectively. Thus, it can provide some guidelines for decision makers when coping with emergency rescue problem with uncertain demand, and offers an excellent reference when issues pertain to bioterrorism.

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

Hussain, Hameed; Malik, Saif Ur Rehman; Hameed, Abdul

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement ofmore » all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.« less

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

Friese, Ryan; Khemka, Bhavesh; Maciejewski, Anthony A

Rising costs of energy consumption and an ongoing effort for increases in computing performance are leading to a significant need for energy-efficient computing. Before systems such as supercomputers, servers, and datacenters can begin operating in an energy-efficient manner, the energy consumption and performance characteristics of the system must be analyzed. In this paper, we provide an analysis framework that will allow a system administrator to investigate the tradeoffs between system energy consumption and utility earned by a system (as a measure of system performance). We model these trade-offs as a bi-objective resource allocation problem. We use a popular multi-objective geneticmore » algorithm to construct Pareto fronts to illustrate how different resource allocations can cause a system to consume significantly different amounts of energy and earn different amounts of utility. We demonstrate our analysis framework using real data collected from online benchmarks, and further provide a method to create larger data sets that exhibit similar heterogeneity characteristics to real data sets. This analysis framework can provide system administrators with insight to make intelligent scheduling decisions based on the energy and utility needs of their systems.« less

A novel dynamic wavelength bandwidth allocation scheme over OFDMA PONs

NASA Astrophysics Data System (ADS)

Yan, Bo; Guo, Wei; Jin, Yaohui; Hu, Weisheng

2011-12-01

With rapid growth of Internet applications, supporting differentiated service and enlarging system capacity have been new tasks for next generation access system. In recent years, research in OFDMA Passive Optical Networks (PON) has experienced extraordinary development as for its large capacity and flexibility in scheduling. Although much work has been done to solve hardware layer obstacles for OFDMA PON, scheduling algorithm on OFDMA PON system is still under primary discussion. In order to support QoS service on OFDMA PON system, a novel dynamic wavelength bandwidth allocation (DWBA) algorithm is proposed in this paper. Per-stream QoS service is supported in this algorithm. Through simulation, we proved our bandwidth allocation algorithm performs better in bandwidth utilization and differentiate service support.

Low-Complexity User Selection for Rate Maximization in MIMO Broadcast Channels with Downlink Beamforming

PubMed Central

Silva, Adão; Gameiro, Atílio

2014-01-01

We present in this work a low-complexity algorithm to solve the sum rate maximization problem in multiuser MIMO broadcast channels with downlink beamforming. Our approach decouples the user selection problem from the resource allocation problem and its main goal is to create a set of quasiorthogonal users. The proposed algorithm exploits physical metrics of the wireless channels that can be easily computed in such a way that a null space projection power can be approximated efficiently. Based on the derived metrics we present a mathematical model that describes the dynamics of the user selection process which renders the user selection problem into an integer linear program. Numerical results show that our approach is highly efficient to form groups of quasiorthogonal users when compared to previously proposed algorithms in the literature. Our user selection algorithm achieves a large portion of the optimum user selection sum rate (90%) for a moderate number of active users. PMID:24574928

Saliency detection algorithm based on LSC-RC

NASA Astrophysics Data System (ADS)

Wu, Wei; Tian, Weiye; Wang, Ding; Luo, Xin; Wu, Yingfei; Zhang, Yu

2018-02-01

Image prominence is the most important region in an image, which can cause the visual attention and response of human beings. Preferentially allocating the computer resources for the image analysis and synthesis by the significant region is of great significance to improve the image area detecting. As a preprocessing of other disciplines in image processing field, the image prominence has widely applications in image retrieval and image segmentation. Among these applications, the super-pixel segmentation significance detection algorithm based on linear spectral clustering (LSC) has achieved good results. The significance detection algorithm proposed in this paper is better than the regional contrast ratio by replacing the method of regional formation in the latter with the linear spectral clustering image is super-pixel block. After combining with the latest depth learning method, the accuracy of the significant region detecting has a great promotion. At last, the superiority and feasibility of the super-pixel segmentation detection algorithm based on linear spectral clustering are proved by the comparative test.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1996-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1998-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

A Climatic Stability Approach to Prioritizing Global Conservation Investments

PubMed Central

Iwamura, Takuya; Wilson, Kerrie A.; Venter, Oscar; Possingham, Hugh P.

2010-01-01

Climate change is impacting species and ecosystems globally. Many existing templates to identify the most important areas to conserve terrestrial biodiversity at the global scale neglect the future impacts of climate change. Unstable climatic conditions are predicted to undermine conservation investments in the future. This paper presents an approach to developing a resource allocation algorithm for conservation investment that incorporates the ecological stability of ecoregions under climate change. We discover that allocating funds in this way changes the optimal schedule of global investments both spatially and temporally. This allocation reduces the biodiversity loss of terrestrial endemic species from protected areas due to climate change by 22% for the period of 2002–2052, when compared to allocations that do not consider climate change. To maximize the resilience of global biodiversity to climate change we recommend that funding be increased in ecoregions located in the tropics and/or mid-elevation habitats, where climatic conditions are predicted to remain relatively stable. Accounting for the ecological stability of ecoregions provides a realistic approach to incorporating climate change into global conservation planning, with potential to save more species from extinction in the long term. PMID:21152095

Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic

PubMed Central

2014-01-01

Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set. PMID:25295295

Energy-saving EPON Bandwidth Allocation Algorithm Supporting ONU's Sleep Mode

NASA Astrophysics Data System (ADS)

Zhang, Yinfa; Ren, Shuai; Liao, Xiaomin; Fang, Yuanyuan

2014-09-01

A new bandwidth allocation algorithm was presented by combining merits of the IPACT algorithm and the cyclic DBA algorithm based on the DBA algorithm for ONU's sleep mode. Simulation results indicate that compared with the normal mode ONU, the ONU's sleep mode can save about 74% of energy. The new algorithm has a smaller average packet delay and queue length in the upstream direction. While in the downstream direction, the average packet delay of the new algorithm is less than polling cycle Tcycle and the average queue length is less than the product of Tcycle and the maximum link rate. The new algorithm achieves a better compromise between energy-saving and ensuring quality of service.

How to allocate limited healthcare resources: Lessons from the introduction of antiretroviral therapy in rural Mozambique

PubMed Central

Dodson, Zan M.; Agadjanian, Victor; Driessen, Julia

2016-01-01

Proper allocation of limited healthcare resources is a challenging task for policymakers in developing countries. Allocation of and access to these resources typically varies based on how need is defined, thus determining how individuals access and acquire healthcare. Using the introduction of antiretroviral therapy in southern Mozambique as an example, we examine alternative definitions of need for rural populations and how they might impact the allocation of this vital health service. Our results show that how need is defined matters when allocating limited healthcare resources and the use of need-based metrics can help ensure more optimal distribution of services. PMID:28596630

Operator Objective Function Guidance for a Real-Time Unmanned Vehicle Scheduling Algorithm

DTIC Science & Technology

2012-12-01

Consensus - Based Decentralized Auctions for Robust Task Allocation ,” IEEE Transactions on Robotics and Automation, Vol. 25, No. 4, No. 4, 2009, pp. 912...planning for the fleet. The decentralized task planner used in OPS-USERS is the consensus - based bundle algorithm (CBBA), a decentralized , polynomial...and surveillance (OPS-USERS), which leverages decentralized algorithms for vehicle routing and task allocation . This

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

NASA Astrophysics Data System (ADS)

Sun, Xiuqiao; Wang, Jian

2018-07-01

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

Resource Allocation and Public Policy in Alberta's Postsecondary System.

ERIC Educational Resources Information Center

Barneston, Bob; Boberg, Alice

2000-01-01

Resource allocation in Alberta's postsecondary system has changed substantially since 1994, designed to reapportion financial responsibility for higher education, increase vocational outcomes of postsecondary education, and increase transfer of knowledge and technology to the private sector. This paper outlines how resource allocation has been…

Phylogeny determines flower size-dependent sex allocation at flowering in a hermaphroditic family.

PubMed

Teixido, A L; Guzmán, B; Staggemeier, V G; Valladares, F

2017-11-01

In animal-pollinated hermaphroditic plants, optimal floral allocation determines relative investment into sexes, which is ultimately dependent on flower size. Larger flowers disproportionally increase maleness whereas smaller and less rewarding flowers favour female function. Although floral traits are considered strongly conserved, phylogenetic relationships in the interspecific patterns of resource allocation to floral sex remain overlooked. We investigated these patterns in Cistaceae, a hermaphroditic family. We reconstructed phylogenetic relationships among Cistaceae species and quantified phylogenetic signal for flower size, dry mass and nutrient allocation to floral structures in 23 Mediterranean species using Blomberg's K-statistic. Lastly, phylogenetically-controlled correlational and regression analyses were applied to examine flower size-based allometry in resource allocation to floral structures. Sepals received the highest dry mass allocation, followed by petals, whereas sexual structures increased nutrient allocation. Flower size and resource allocation to floral structures, except for carpels, showed a strong phylogenetic signal. Larger-flowered species allometrically allocated more resources to maleness, by increasing allocation to corollas and stamens. Our results suggest a major role of phylogeny in determining interspecific changes in flower size and subsequent floral sex allocation. This implies that flower size balances the male-female function over the evolutionary history of Cistaceae. While allometric resource investment in maleness is inherited across species diversification, allocation to the female function seems a labile trait that varies among closely related species that have diversified into different ecological niches. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

On System Engineering a Barter-Based Re-allocation of Space System Key Development Resources

NASA Astrophysics Data System (ADS)

Kosmann, William J.

NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level development cost growths ranging from 23 to 77%. A new study of 26 historical NASA science instrument set developments using expert judgment to re-allocate key development resources has an average cost growth of 73.77%. Twice in history, during the Cassini and EOS-Terra science instrument developments, a barter-based mechanism has been used to re-allocate key development resources. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to re-allocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource re-allocation simulation was used to perform 300 instrument development simulations, using barter to re-allocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource re-allocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource re-allocation should work on science spacecraft development as well as it has worked on science instrument development. A new study of 28 historical NASA science spacecraft developments has an average cost growth of 46.04%. As barter-based key development resource re-allocation has never been tried in a spacecraft development, no historical results exist, and an inference on the means test is not possible. A simulation of using barter-based resource re-allocation should be developed. The NetLogo instrument development simulation should be modified to account for spacecraft development market participant differences. The resulting agent-based barter-based spacecraft resource re-allocation simulation would then be used to determine if significant statistical evidence exists to prove a claim that using barter-based resource re-allocation will result in lower expected cost growth.

Equity in resource allocation for health: a comparative study of the Ashanti and Northern Regions of Ghana.

PubMed

Asante, Augustine Danso; Zwi, Anthony Barry; Ho, Maria Theresa

2006-10-01

Debate over the equitable allocation of financial resources in the health sector has focused overwhelmingly on allocation from national to regional levels. More equitable allocation of such resources within regions has been virtually ignored, creating a vacuum in knowledge regarding how resources are allocated intra-regionally and their potential influence on promoting health equity. In this paper, we report an empirical study examining progress towards equity in intra-regional resource allocation in the Ashanti and Northern regions of Ghana. Relative deprivation across the 31 districts of the two regions was measured as a proxy of health needs. The result was used to develop an equity-adjusted share index (EAS) applied as a yardstick against which progress towards equity was assessed. The study found a significant correlation between districts' share of donor pooled funds (DPF) and the EAS in the Northern region for three of the 4 years investigated. In Ashanti region, a worsening trend in relation to equity in DPF allocation was discovered. The proportion of variance in the share of DPF that could be explained by the EAS reduced incrementally from 56% in 1999 to less than 1% in 2002. The study highlights the need for more emphasis on intra-regional equity in resource allocation in Ghana.

Resource allocation for mitigating regional air pollution–related mortality: A summertime case study for five cities in the United States

PubMed Central

Liao, Kuo-Jen; Hou, Xiangting; Strickland, Matthew J.

2016-01-01

ABSTRACT An important issue of regional air quality management is to allocate air quality management funds to maximize environmental and human health benefits. In this study, we use an innovative approach to tackle this air quality management issue. We develop an innovative resource allocation model that allows identification of air pollutant emission control strategies that maximize mortality avoidances subject to a resource constraint. We first present the development of the resource allocation model and then a case study to show how the model can be used to identify resource allocation strategies that maximize mortality avoidances for top five Metropolitan Statistical Areas (MSAs) (i.e., New York, Los Angeles, Chicago, Dallas-Fort Worth, and Philadelphia) in the continental United States collectively. Given budget constraints in the U.S. Environmental Protection Agency’s (EPA) Clean Air Act assessment, the results of the case study suggest that controls of sulfur dioxide (SO2) and primary carbon (PC) emissions from EPA Regions 2, 3, 5, 6, and 9 would have significant health benefits for the five selected cities collectively. Around 30,800 air pollution–related mortalities could be avoided during the selected 2-week summertime episode for the five cities collectively if the budget could be allocated based on the results of the resource allocation model. Although only five U.S. cities during a 2-week episode are considered in the case study, the resource allocation model can be used by decision-makers to plan air pollution mitigation strategies to achieve the most significant health benefits for other seasons and more cities over a region or the continental U.S.Implications: Effective allocations of air quality management resources are challenging and complicated, and it is desired to have a tool that can help decision-makers better allocate the funds to maximize health benefits of air pollution mitigation. An innovative resource allocation model developed in this study can help decision-makers identify the best resource allocation strategies for multiple cities collectively. The results of a case study suggest that controls of primary carbon and sulfur dioxides emissions would achieve the most significant health benefits for five selected cities collectively. PMID:27441782

Calculation method of water injection forward modeling and inversion process in oilfield water injection network

NASA Astrophysics Data System (ADS)

Liu, Long; Liu, Wei

2018-04-01

A forward modeling and inversion algorithm is adopted in order to determine the water injection plan in the oilfield water injection network. The main idea of the algorithm is shown as follows: firstly, the oilfield water injection network is inversely calculated. The pumping station demand flow is calculated. Then, forward modeling calculation is carried out for judging whether all water injection wells meet the requirements of injection allocation or not. If all water injection wells meet the requirements of injection allocation, calculation is stopped, otherwise the demand injection allocation flow rate of certain step size is reduced aiming at water injection wells which do not meet requirements, and next iterative operation is started. It is not necessary to list the algorithm into water injection network system algorithm, which can be realized easily. Iterative method is used, which is suitable for computer programming. Experimental result shows that the algorithm is fast and accurate.

Children's understanding of equity in the context of inequality.

PubMed

Rizzo, Michael T; Killen, Melanie

2016-11-01

In the context of a pre-existing resource inequality, the concerns for strict equality (allocating the same number of resources to all recipients) conflict with the concerns for equity (allocating resources to rectify the inequality). This study demonstrated age-related changes in children's (3-8 years old, N = 133) ability to simultaneously weigh the concerns for equality and equity through the analysis of children's judgements, allocations, and reasoning in the context of a pre-existing inequality. Three- to 4-year-olds took equity into account in their judgements of allocations, but allocated resources equally in a behavioural task. In contrast, 5- to 6-year-olds rectified the inequality in their allocations, but judged both equitable and equal allocations to be fair. It was not until 7-8 years old that children focused on rectifying the inequality in their allocations and judgements, as well as judged equal allocations less positively than equitable allocations, thereby demonstrating a more complete understanding of the necessity of rectifying inequalities. The novel findings revealed age-related changes from 3 to 8 years old regarding how the concerns for equity and equality develop, and how children's judgements, allocations, and reasoning are coordinated when making allocation decisions. © 2016 The British Psychological Society.

Intelligence Level and the Allocation of Resources for Creative Tasks: A Pupillometry Study

ERIC Educational Resources Information Center

Ojha, Amitash; Indurkhya, Bipin; Lee, Minho

2017-01-01

This pupillometry study examined the relationship between intelligence and creative cognition from the resource allocation perspective. It was hypothesized that, during a creative metaphor task, individuals with higher intelligence scores would have different resource allocation patterns than individuals with lower intelligence scores. The study…

Allocating Resources for Learning Support: A Case Study.

ERIC Educational Resources Information Center

Sharp, Stephen

2000-01-01

Examines how learning-support resources are allocated to Scottish secondary schools, drawing on data from an Edinburgh education authority. Although a rationale for allocating resources based on socioeconomic indices can be constructed, basing decisions on a combination of standardized attainment tests and special-needs audits is preferable.…

Resource Allocation in British Universities. SRHE Monograph 56.

ERIC Educational Resources Information Center

Shattock, Michael, Ed.; Rigby, Gwynneth, Ed.

The ways that British universities allocate their resources are discussed, with attention to different styles, techniques, and decison-making structures. Since the purpose is to describe institutional models of resource allocation, specific universities are not identified by name. After identifying the sources of income and the breakdown of…

Stigmatizing attitudes about mental illness and allocation of resources to mental health services.

PubMed

Corrigan, Patrick W; Watson, Amy C; Warpinski, Amy C; Gracia, Gabriela

2004-08-01

This study tests a social psychological model (Skitka & Tetlock, 1992). Journal of Experimental Social Psychology, 28, 491-522; [1993]. Journal of Personality & Social Psychology, 65, 1205-1223 stating that policy maker decisions regarding the allocation of resources to mental health services are influenced by their attitudes towards people with mental illness and treatment efficacy. Fifty four individuals participated in a larger study of education about mental health stigma. Participants completed various measures of resource allocation preferences for mandated treatment and rehabilitation services, attributions about people with mental illness, and factors that influence allocation preferences including perceived treatment efficacy. Results showed significant attitudinal correlates with resource allocation preferences for mandated treatment, but no correlates to rehabilitation services. In particular, people who pity people with mental illness as well as those that endorse coercive and segregated treatments, were more likely to rate resource allocation to mandated care as important. Perceived treatment efficacy was also positively associated with resource allocation preferences for mandated treatment. A separate behavioral measure that involved donating money to NAMI was found to be inversely associated with blaming people for their mental illness and not being willing to help them. Implications of these findings on strategies that seek to increase resources for mental health programs are discussed.

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies.

PubMed

Ng'oma, Enoch; Perinchery, Anna M; King, Elizabeth G

2017-06-28

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. © 2017 The Author(s).

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

PubMed Central

2017-01-01

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the ‘omic’ opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory. PMID:28637856

Multi-heuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed system

PubMed Central

Page, Andrew J.; Keane, Thomas M.; Naughton, Thomas J.

2010-01-01

We present a multi-heuristic evolutionary task allocation algorithm to dynamically map tasks to processors in a heterogeneous distributed system. It utilizes a genetic algorithm, combined with eight common heuristics, in an effort to minimize the total execution time. It operates on batches of unmapped tasks and can preemptively remap tasks to processors. The algorithm has been implemented on a Java distributed system and evaluated with a set of six problems from the areas of bioinformatics, biomedical engineering, computer science and cryptography. Experiments using up to 150 heterogeneous processors show that the algorithm achieves better efficiency than other state-of-the-art heuristic algorithms. PMID:20862190

Rate distortion optimal bit allocation methods for volumetric data using JPEG 2000.

PubMed

Kosheleva, Olga M; Usevitch, Bryan E; Cabrera, Sergio D; Vidal, Edward

2006-08-01

Computer modeling programs that generate three-dimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

PubMed

Pan, Ian; Nolan, Laura B; Brown, Rashida R; Khan, Romana; van der Boor, Paul; Harris, Daniel G; Ghani, Rayid

2017-06-01

To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based risk assessment. We compared different models and determined the strongest predictors of adverse birth outcomes using positive predictive value as the metric for selection. Machine learning algorithms performed similarly, outperforming the current paper-based risk assessment by up to 36%; a refined paper-based assessment outperformed the current assessment by up to 22%. We estimate that these improvements will allow 100 to 170 additional high-risk pregnant women screened for program eligibility each year to receive services that would have otherwise been unobtainable. Our analysis exhibits the potential for machine learning to move government agencies toward a more data-informed approach to evaluating risk and providing social services. Overall, such efforts will improve the efficiency of allocating resource-intensive interventions.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Evaluation of health resource utilization efficiency in community health centers of Jiangsu Province, China.

PubMed

Xu, Xinglong; Zhou, Lulin; Antwi, Henry Asante; Chen, Xi

2018-02-20

While the demand for health services keep escalating at the grass roots or rural areas of China, a substantial portion of healthcare resources remain stagnant in the more developed cities and this has entrenched health inequity in many parts of China. At its conception, China's Deepen Medical Reform started in 2012 was intended to flush out possible disparities and promote a more equitable and efficient distribution of healthcare resources. Nearly half a decade of this reform, there are uncertainties as to whether the attainment of the objectives of the reform is in sight. Using a hybrid of panel data analysis and an augmented data envelopment analysis (DEA), we model human resources, material, finance to determine their technical and scale efficiency to comprehensively evaluate the transverse and longitudinal allocation efficiency of community health resources in Jiangsu Province. We observed that the Deepen Medical Reform in China has led to an increase concern to ensure efficient allocation of community health resources by health policy makers in the province. This has led to greater efficiency in health resource allocation in Jiangsu in general but serious regional or municipal disparities still exist. Using the DEA model, we note that the output from the Community Health Centers does not commensurate with the substantial resources (human resources, materials, and financial) invested in them. We further observe that the case is worst in less-developed Northern parts of Jiangsu Province. The government of Jiangsu Province could improve the efficiency of health resource allocation by improving the community health service system, rationalizing the allocation of health personnel, optimizing the allocation of material resources, and enhancing the level of health of financial resource allocation.

Resource allocation processes at multilateral organizations working in global health

PubMed Central

Chi, Y-Ling; Bump, Jesse B

2018-01-01

Abstract International institutions provide well over US$10 billion in development assistance for health (DAH) annually and between 1990 and 2014, DAH disbursements totaled $458 billion but how do they decide who gets what, and for what purpose? In this article, we explore how allocation decisions were made by the nine convening agencies of the Equitable Access Initiative. We provide clear, plain language descriptions of the complete process from resource mobilization to allocation for the nine multilateral agencies with prominent agendas in global health. Then, through a comparative analysis we illuminate the choices and strategies employed in the nine international institutions. We find that resource allocation in all reviewed institutions follow a similar pattern, which we categorized in a framework of five steps: strategy definition, resource mobilization, eligibility of countries, support type and funds allocation. All the reviewed institutions generate resource allocation decisions through well-structured and fairly complex processes. Variations in those processes seem to reflect differences in institutional principles and goals. However, these processes have serious shortcomings. Technical problems include inadequate flexibility to account for or meet country needs. Although aid effectiveness and value for money are commonly referenced, we find that neither performance nor impact is a major criterion for allocating resources. We found very little formal consideration of the incentives generated by allocation choices. Political issues include non-transparent influence on allocation processes by donors and bureaucrats, and the common practice of earmarking funds to bypass the normal allocation process entirely. Ethical deficiencies include low accountability and transparency at international institutions, and limited participation by affected citizens or their representatives. We find that recipient countries have low influence on allocation processes themselves, although within these processes they have some influence in relatively narrow areas. PMID:29415239

Protecting resources for primary health care under fiscal federalism: options for resource allocation.

PubMed

Okorafor, Okore A; Thomas, Stephen

2007-11-01

The introduction of fiscal federalism or decentralization of functions to lower levels of government is a reform not done primarily with health sector concerns. A major concern for the health sector is that devolution of expenditure responsibilities to sub-national levels of government can adversely affect the equitable distribution of financial resources across local jurisdictions. Since the adoption of fiscal federalism in South Africa, progress towards achieving a more equitable distribution of public sector health resources (financial) has slowed down considerably. This study attempts to identify appropriate resource allocation mechanisms under the current South African fiscal federal system that could be employed to promote equity in primary health care (PHC) allocations across provinces and districts. The study uses data from interviews with government officials involved in the budgeting and resource allocation process for PHC, literature on fiscal federalism and literature on international experience to inform analysis and recommendations. The results from the study identify historical incremental budgeting, weak managerial capacity at lower levels of government, poor accounting of PHC expenditure, and lack of protection for PHC funds as constraints to the realization of a more equitable distribution of PHC allocations. Based on interview data, no one resource allocation mechanism received unanimous support from stakeholders. However, the study highlights the particularly high level of autonomy enjoyed by provincial governments with regards to decision making for allocations to health and PHC services as the major constraint to achieving a more equitable distribution of PHC resources. The national government needs to have more involvement in decision making for resource allocation to PHC services if significant progress towards equity is to be achieved.

Identifying individuals for primary cardiovascular disease prevention in UK general practice: priorities and resource implications

PubMed Central

Holt, Tim A; Thorogood, Margaret; Griffiths, Frances; Munday, Stephen; Stables, David

2008-01-01

Targeted cardiovascular disease prevention relies on risk-factor information held in primary care records. A risk algorithm, the ‘e-Nudge’, was applied to data from a population of ≥50-year-olds in 19 West Midlands practices, to identify those individuals at risk of cardiovascular disease. Altogether, 5.9% were identified aged 50–74 years at ≥20% 10-year risk based on existing data, and a further 26.4% were potentially at risk but had missing risk-factor information; 9.2% of patients aged over 50 years with established cardiovascular disease had at least one modifiable risk factor outside the audit target of the Quality and Outcomes Framework. Implications for resource allocation are discussed. PMID:18611316

Differentiated protection services with failure probability guarantee for workflow-based applications

NASA Astrophysics Data System (ADS)

Zhong, Yaoquan; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2010-12-01

A cost-effective and service-differentiated provisioning strategy is very desirable to service providers so that they can offer users satisfactory services, while optimizing network resource allocation. Providing differentiated protection services to connections for surviving link failure has been extensively studied in recent years. However, the differentiated protection services for workflow-based applications, which consist of many interdependent tasks, have scarcely been studied. This paper investigates the problem of providing differentiated services for workflow-based applications in optical grid. In this paper, we develop three differentiated protection services provisioning strategies which can provide security level guarantee and network-resource optimization for workflow-based applications. The simulation demonstrates that these heuristic algorithms provide protection cost-effectively while satisfying the applications' failure probability requirements.

Toward a Multilevel Perspective on the Allocation of Educational Resources.

ERIC Educational Resources Information Center

Monk, David H.

1981-01-01

The importance of the following is demonstrated: (1) striking a balance between the attention given to resource allocation practices at macro compared to microlevels of decision making; and (2) learning more about how resource allocation decisions made at one level affect practices at other levels of the educational system. (Author/GK)

The Effects of Charter School Competition on School District Resource Allocation

ERIC Educational Resources Information Center

Arsen, David; Ni, Yongmei

2012-01-01

Purpose: This article examines two questions: (a) How does resource allocation change in school districts experiencing sustained charter school competition? (b) Among districts exposed to charter competition, are there differences in the resource allocation adjustments between those that do and do not succeed in stemming further enrollment loss to…

Minority Threat, Crime Control, and Police Resource Allocation in the Southwestern United States

ERIC Educational Resources Information Center

Holmes, Malcolm D.; Smith, Brad W.; Freng, Adrienne B.; Munoz, Ed A.

2008-01-01

Numerous studies have examined political influences on communities' allocations of fiscal and personnel resources to policing. Rational choice theory maintains that these resources are distributed in accordance with the need for crime control, whereas conflict theory argues that they are allocated with the aim of controlling racial and ethnic…

FOR Allocation to Distribution Systems based on Credible Improvement Potential (CIP)

NASA Astrophysics Data System (ADS)

Tiwary, Aditya; Arya, L. D.; Arya, Rajesh; Choube, S. C.

2017-02-01

This paper describes an algorithm for forced outage rate (FOR) allocation to each section of an electrical distribution system subject to satisfaction of reliability constraints at each load point. These constraints include threshold values of basic reliability indices, for example, failure rate, interruption duration and interruption duration per year at load points. Component improvement potential measure has been used for FOR allocation. Component with greatest magnitude of credible improvement potential (CIP) measure is selected for improving reliability performance. The approach adopted is a monovariable method where one component is selected for FOR allocation and in the next iteration another component is selected for FOR allocation based on the magnitude of CIP. The developed algorithm is implemented on sample radial distribution system.

Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

PubMed

Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend

2011-10-11

In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.

How resource allocation decisions are made in the health care market.

PubMed

Vogel, W B

2000-10-01

This paper describes how economists view resource allocation decisions in health care markets. The basic economic decisions that must be made in any economic system and the resource allocation decisions in a perfectly competitive market are described. An idealized market can achieve an efficient allocation of resources and is contrasted with a more realistic description of the numerous ways in which health care markets depart from the perfectly competitive ideal. The implications of these departures for health care policy are discussed, along with key controversies concerning reliance upon markets for resource allocation in health care. In particular, the failure of competitive markets to achieve what many consider an equitable distribution of health care is emphasized. The paper concludes with some practical observations on how pharmacists can use the increasing emphasis on economic efficiency to the advantage of their profession.

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

NASA Technical Reports Server (NTRS)

Bloem, Michael; Drew, Michael; Lai, Chok Fung; Bilimoria, Karl D.

2012-01-01

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Suggestions to ameliorate the inequity in urban/rural allocation of healthcare resources in China.

PubMed

Chen, Yiyi; Yin, Zhou; Xie, Qiong

2014-05-01

The imbalance in the allocation in healthcare resources between urban and rural areas has become a main focus of the recent medical reforms adopted in China. However, systematic analysis has identified wide differences in the allocation of healthcare resources between urban and rural areas, including healthcare expenditures and the number of healthcare facilities, available beds, and personnel. Therefore, the aim of this report was to identify ethical considerations in current governmental policies to rectify existing problems in the distribution of healthcare resources. Our findings indicate that the inequality in the distribution of healthcare resources does not adhere to ethical standards and the policies are flawed because they give rise to differences in the availability of medical care to urban and rural communities. To optimize the allocation of medical healthcare resources, countermeasures are proposed to formulate policies to urge the flow of public healthcare resources to rural areas, strengthen the responsibilities of both governmental and public financial investments, increase the construction of public healthcare facilities in rural areas, promote the quality of healthcare resources, adjust resource allocations to rural public healthcare facilities, and improve resource utilization efficiency by establishing two-way referral mechanisms.

Tactical resource allocation and elective patient admission planning in care processes.

PubMed

Hulshof, Peter J H; Boucherie, Richard J; Hans, Erwin W; Hurink, Johann L

2013-06-01

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to meet production targets/to serve the strategically agreed number of patients, and to use resources efficiently. This paper proposes a method to develop a tactical resource allocation and elective patient admission plan. These tactical plans allocate available resources to various care processes and determine the selection of patients to be served that are at a particular stage of their care process. Our method is developed in a Mixed Integer Linear Programming (MILP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital, thereby integrating decision making for a chain of hospital resources. Computational results indicate that our method leads to a more equitable distribution of resources and provides control of patient access times, the number of patients served and the fraction of allocated resource capacity. Our approach is generic, as the base MILP and the solution approach allow for including various extensions to both the objective criteria and the constraints. Consequently, the proposed method is applicable in various settings of tactical hospital management.

Placental Growth Factor (PlGF) in Women with Suspected Pre-Eclampsia Prior to 35 Weeks’ Gestation: A Budget Impact Analysis

PubMed Central

Duckworth, Suzy; Seed, Paul T.; Mackillop, Lucy; Shennan, Andrew H.; Hunter, Rachael

2016-01-01

Objective To model the resource implications of placental growth factor (PlGF) testing in women with suspected pre-eclampsia prior to 35 weeks’ gestation as part of a management algorithm, compared with current practice. Methods Data on resource use from 132 women with suspected pre-eclampsia prior to 35 weeks’ gestation, enrolled in a prospective observational cohort study evaluating PlGF measurement within antenatal assessment units within two UK consultant-led maternity units was extracted by case note review. A decision analytic model was developed using these data to establish the budget impact of managing women with suspected pre-eclampsia for two weeks from the date of PlGF testing, using a clinical management algorithm and reference cost tariffs. The main outcome measures of resource use (numbers of outpatient appointments, ultrasound investigations and hospital admissions) were correlated to final diagnosis and used to calculate comparative management regimes. Results The mean cost saving associated with the PlGF test (in the PlGF plus management arm) was £35,087 (95% CI -£33,181 to -£36,992) per 1,000 women. This equated to a saving of £582 (95% CI -552 to -£613) per woman tested. In 94% of iterations, PlGF testing was associated with cost saving compared to current practice. Conclusions This analysis suggests PlGF used as part of a clinical management algorithm in women presenting with suspected pre-eclampsia prior to 35 weeks’ gestation could provide cost savings by reducing unnecessary resource use. Introduction of PlGF testing could be used to direct appropriate resource allocation and overall would be cost saving. PMID:27741259

Rationing of resources: ethical issues in disasters and epidemic situations.

PubMed

Lin, Janet Y; Anderson-Shaw, Lisa

2009-01-01

In an epidemic situation or large-scale disaster, medical and human resources may be stretched to the point of exhaustion. Appropriate planning must incorporate plans of action that minimize public health morbidity and mortality while maximizing the appropriate use of medical and human healthcare resources. While the current novel H1N1 influenza has spread throughout the world, the severity of this strain of influenza appears to be relatively less virulent and lethal compared to the 1918 influenza pandemic. However, the presence of this new influenza strain has reignited interest in pandemic planning. Amongst other necessary resources needed to combat pandemic influenza, a major medical resource concern is the limited number of mechanical ventilators that would be available to be used to treat ill patients. Recent reported cases of avian influenza suggest that mechanical ventilation will be required for the successful recovery of many individuals ill with this strain of virus. However, should the need for ventilators exceed the number of available machines, how will care providers make the difficult ethical decisions as to who should be placed or who should remain on these machines as more influenza patients arrive in need of care? This paper presents a decision-making model for clinicians that is based upon the bioethical principles of beneficence and justice. The model begins with the basic assumptions of triage and progresses into a useful algorithm based upon utilitarian principles. The model is intended to be used as a guide for clinicians in making decisions about the allocation of scarce resources in a just manner and to serve as an impetus for institutions to create or adapt plans to address resource allocation issues should the need arise.

Complexity as a Factor of Quality and Cost in Large Scale Software Development.

DTIC Science & Technology

1979-12-01

allocating testing resources." [69 69I V. THE ROLE OF COMPLEXITY IN RESOURCE ESTIMATION AND ALLOCATION A. GENERAL It can be argued that blame for the...and allocation of testing resource by - identifying independent substructures and - identifying heavily used logic paths. 2. Setting a Design Threshold... RESOURCE ESTIMATION -------- 70 1. New Dynamic Field ------------------------- 70 2. Quality and Testing ----------------------- 71 3. Programming Units of

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

NASA Astrophysics Data System (ADS)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Playing Games with Optimal Competitive Scheduling

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Crawford, James; Khatib, Lina; Brafman, Ronen

2005-01-01

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, selfish preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource.

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions

PubMed Central

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time. PMID:28118384

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions.

PubMed

Guerrero, Jose; Oliver, Gabriel; Valero, Oscar

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time.

Benefit of adaptive FEC in shared backup path protected elastic optical network.

PubMed

Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

2015-07-27

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

HIV epidemic control-a model for optimal allocation of prevention and treatment resources.

PubMed

Alistar, Sabina S; Long, Elisa F; Brandeau, Margaret L; Beck, Eduard J

2014-06-01

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

30 CFR 1206.459 - Allocation of washed coal.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Allocation of washed coal. 1206.459 Section... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.459 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

30 CFR 1206.459 - Allocation of washed coal.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Allocation of washed coal. 1206.459 Section... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.459 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

30 CFR 1206.260 - Allocation of washed coal.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Allocation of washed coal. 1206.260 Section... INTERIOR Natural Resources Revenue PRODUCT VALUATION Federal Coal § 1206.260 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was...

30 CFR 1206.260 - Allocation of washed coal.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Allocation of washed coal. 1206.260 Section... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.260 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

30 CFR 1206.459 - Allocation of washed coal.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Allocation of washed coal. 1206.459 Section... INTERIOR Natural Resources Revenue PRODUCT VALUATION Indian Coal § 1206.459 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was...

30 CFR 1206.260 - Allocation of washed coal.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Allocation of washed coal. 1206.260 Section... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.260 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

30 CFR 1206.459 - Allocation of washed coal.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Allocation of washed coal. 1206.459 Section... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.459 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

30 CFR 1206.260 - Allocation of washed coal.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Allocation of washed coal. 1206.260 Section... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.260 Allocation of washed coal. (a) When coal is subjected to washing, the washed coal must be allocated to the leases from which it was extracted. (b) When...

Space Station Freedom resource allocation accommodation of technology payload requirements

NASA Technical Reports Server (NTRS)

Avery, Don E.; Collier, Lisa D.; Gartrell, Charles F.

1990-01-01

An overview of the Office of Aeronautics, Exploration, and Technology (OAET) Space Station Freedom Technology Payload Development Program is provided, and the OAET Station resource requirements are reviewed. The requirements are contrasted with current proposed resource allocations. A discussion of the issues and conclusions are provided. It is concluded that an overall 20 percent resource allocation is appropriate to support OAET's technology development program, that some resources are inadequate even at the 20 percent level, and that bartering resources among U.S. users and international partners and increasing the level of automation may be viable solutions to the resource constraint problem.

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

Risk-based decision making for staggered bioterrorist attacks : resource allocation and risk reduction in "reload" scenarios.

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

Lemaster, Michelle Nicole; Gay, David M.; Ehlen, Mark Andrew

2009-10-01

Staggered bioterrorist attacks with aerosolized pathogens on population centers present a formidable challenge to resource allocation and response planning. The response and planning will commence immediately after the detection of the first attack and with no or little information of the second attack. In this report, we outline a method by which resource allocation may be performed. It involves probabilistic reconstruction of the bioterrorist attack from partial observations of the outbreak, followed by an optimization-under-uncertainty approach to perform resource allocations. We consider both single-site and time-staggered multi-site attacks (i.e., a reload scenario) under conditions when resources (personnel and equipment whichmore » are difficult to gather and transport) are insufficient. Both communicable (plague) and non-communicable diseases (anthrax) are addressed, and we also consider cases when the data, the time-series of people reporting with symptoms, are confounded with a reporting delay. We demonstrate how our approach develops allocations profiles that have the potential to reduce the probability of an extremely adverse outcome in exchange for a more certain, but less adverse outcome. We explore the effect of placing limits on daily allocations. Further, since our method is data-driven, the resource allocation progressively improves as more data becomes available.« less

Where Does the Money Go? Resource Allocation in Elementary and Secondary Education.

ERIC Educational Resources Information Center

Picus, Lawrence O., Ed.; Wattenbarger, James L., Ed.

The 13 Chapters in this book address the important issue of how schools and school districts allocate their resources. The book summarizes the emerging research in educational resource allocations (tax dollars) at the district, school, and classroom levels. Following the preface by Lawrence O. Picus, the chapters include: (1) "Why Do We Need to…

Allocation Anatomy: How District Policies That Deploy Resources Can Support (or Undermine) District Reform Strategies

ERIC Educational Resources Information Center

Roza, Marguerite

2008-01-01

The goal of this paper is to explore the effects of micro-budgeting decisions and show how they might support or hamper district reform strategies. The study draws on public and private sector resource allocation literature to identify key elements of resource allocation decisions. These elements are used to highlight different allocation…

A Model of Resource Allocation in Public School Districts: A Theoretical and Empirical Analysis.

ERIC Educational Resources Information Center

Chambers, Jay G.

This paper formulates a comprehensive model of resource allocation in a local public school district. The theoretical framework specified could be applied equally well to any number of local public social service agencies. Section 1 develops the theoretical model describing the process of resource allocation. This involves the determination of the…

Resource Allocation Models and Accountability: A Jamaican Case Study

ERIC Educational Resources Information Center

Nkrumah-Young, Kofi K.; Powell, Philip

2008-01-01

Higher education institutions (HEIs) may be funded privately, by the state or by a mixture of the two. Nevertheless, any state financing of HE necessitates a mechanism to determine the level of support and the channels through which it is to be directed; that is, a resource allocation model. Public funding, through resource allocation models,…

Rail-Highway Crossing Resource Allocation Procedure - User's Guide. Third Edition

DOT National Transportation Integrated Search

1987-08-01

To assist states and railroads in determining effective allocations of Federal funds for rail-highway crossing improvements, the U.S. Department of Transportation has developed the DOT Rail-Highway Crossing Resource Allocation Procedure. The procedur...

The dynamics of resource allocation and costs of reproduction in a sexually dimorphic, wind-pollinated dioecious plant.

PubMed

Teitel, Z; Pickup, M; Field, D L; Barrett, S C H

2016-01-01

Sexual dimorphism in resource allocation is expected to change during the life cycle of dioecious plants because of temporal differences between the sexes in reproductive investment. Given the potential for sex-specific differences in reproductive costs, resource availability may contribute to variation in reproductive allocation in females and males. Here, we used Rumex hastatulus, a dioecious, wind-pollinated annual plant, to investigate whether sexual dimorphism varies with life-history stage and nutrient availability, and determine whether allocation patterns differ depending on reproductive commitment. To examine if the costs of reproduction varied between the sexes, reproduction was either allowed or prevented through bud removal, and biomass allocation was measured at maturity. In a second experiment to assess variation in sexual dimorphism across the life cycle, and whether this varied with resource availability, plants were grown in high and low nutrients and allocation to roots, aboveground vegetative growth and reproduction were measured at three developmental stages. Males prevented from reproducing compensated with increased above- and belowground allocation to a much larger degree than females, suggesting that male reproductive costs reduce vegetative growth. The proportional allocation to roots, reproductive structures and aboveground vegetative growth varied between the sexes and among life-cycle stages, but not with nutrient treatment. Females allocated proportionally more resources to roots than males at peak flowering, but this pattern was reversed at reproductive maturity under low-nutrient conditions. Our study illustrates the importance of temporal dynamics in sex-specific resource allocation and provides support for high male reproductive costs in wind-pollinated plants. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.

Resource allocation and budgetary mechanisms for decentralized health systems: experiences from Balochistan, Pakistan.

PubMed

Green, A; Ali, B; Naeem, A; Ross, D

2000-01-01

This paper identifies key political and technical issues involved in the development of an appropriate resource allocation and budgetary system for the public health sector, using experience gained in the Province of Balochistan, Pakistan. The resource allocation and budgetary system is a critical, yet often neglected, component of any decentralization policy. Current systems are often based on historical incrementalism that is neither efficient nor equitable. This article describes technical work carried out in Balochistan to develop a system of resource allocation and budgeting that is needs-based, in line with policies of decentralization, and implementable within existing technical constraints. However, the development of technical systems, while necessary, is not a sufficient condition for the implementation of a resource allocation and decentralized budgeting system. This is illustrated by analysing the constraints that have been encountered in the development of such a system in Balochistan.

A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.

PubMed

Reimers, Alexandra-M; Lindhorst, Henning; Waldherr, Steffen

2017-09-06

In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now. This paper presents step-by-step instructions for building a (dynamic) resource allocation model, starting with prerequisites such as a genome-scale metabolic reconstruction, through building protein and noncatalytic biomass synthesis reactions and assigning turnover rates for each reaction. In addition, we explain how one can use SBML level 3 in combination with the flux balance constraints and our resource allocation modeling annotation to represent such models.

Resource allocation and budgetary mechanisms for decentralized health systems: experiences from Balochistan, Pakistan.

PubMed Central

Green, A.; Ali, B.; Naeem, A.; Ross, D.

2000-01-01

This paper identifies key political and technical issues involved in the development of an appropriate resource allocation and budgetary system for the public health sector, using experience gained in the Province of Balochistan, Pakistan. The resource allocation and budgetary system is a critical, yet often neglected, component of any decentralization policy. Current systems are often based on historical incrementalism that is neither efficient nor equitable. This article describes technical work carried out in Balochistan to develop a system of resource allocation and budgeting that is needs-based, in line with policies of decentralization, and implementable within existing technical constraints. However, the development of technical systems, while necessary, is not a sufficient condition for the implementation of a resource allocation and decentralized budgeting system. This is illustrated by analysing the constraints that have been encountered in the development of such a system in Balochistan. PMID:10994286

Supporting capacity sharing in the cloud manufacturing environment based on game theory and fuzzy logic

NASA Astrophysics Data System (ADS)

Argoneto, Pierluigi; Renna, Paolo

2016-02-01

This paper proposes a Framework for Capacity Sharing in Cloud Manufacturing (FCSCM) able to support the capacity sharing issue among independent firms. The success of geographical distributed plants depends strongly on the use of opportune tools to integrate their resources and demand forecast in order to gather a specific production objective. The framework proposed is based on two different tools: a cooperative game algorithm, based on the Gale-Shapley model, and a fuzzy engine. The capacity allocation policy takes into account the utility functions of the involved firms. It is shown how the capacity allocation policy proposed induces all firms to report truthfully their information about their requirements. A discrete event simulation environment has been developed to test the proposed FCSCM. The numerical results show the drastic reduction of unsatisfied capacity obtained by the model of cooperation implemented in this work.

Research status of multi - robot systems task allocation and uncertainty treatment

NASA Astrophysics Data System (ADS)

Li, Dahui; Fan, Qi; Dai, Xuefeng

2017-08-01

The multi-robot coordination algorithm has become a hot research topic in the field of robotics in recent years. It has a wide range of applications and good application prospects. This paper analyzes and summarizes the current research status of multi-robot coordination algorithms at home and abroad. From task allocation and dealing with uncertainty, this paper discusses the multi-robot coordination algorithm and presents the advantages and disadvantages of each method commonly used.

Evaluation on equality and efficiency of health resources allocation and health services utilization in China.

PubMed

Sun, Jian; Luo, Hongye

2017-07-14

China is faced with a daunting challenge to equality and efficiency in health resources allocation and health services utilization in the context of rapid economic growth. This study sought to evaluate the equality and efficiency of health resources allocation and health services utilization in China. Demographic, economic, and geographic area data was sourced from China Statistical Yearbook 2012-2016. Data related to health resources and health services was obtained from China Health Statistics Yearbook 2012-2016. Furthermore, we evaluated the equality of health resources allocation based on Gini coefficient. Concentration index was used to measure the equality in utilization of health services. Data envelopment analysis (DEA) was employed to assess the efficiency of health resources allocation. From 2011 to 2015, the Gini coefficients for health resources by population ranged between 0.0644 and 0.1879, while the Gini coefficients for the resources by geographic area ranged from 0.6136 to 0.6568. Meanwhile, the concentration index values for health services utilization ranged from -0.0392 to 0.2110. Moreover, in 2015, 10 provinces (32.26%) were relatively efficient in terms of health resources allocation, while 7 provinces (22.58%) and 14 provinces (45.16%) were weakly efficient and inefficient, respectively. There exist distinct regional disparities in the distribution of health resources in China, which are mainly reflected in the geographic distribution of health resources. Furthermore, the people living in the eastern developed areas are more likely to use outpatient care, while the people living in western underdeveloped areas are more likely to use inpatient care. Moreover, the efficiency of health resources allocation in 21 provinces (67.74%) of China was low and needs to be improved. Thus, the government should pay more attention to the equality based on geographic area, guide patients to choose medical treatment rationally, and optimize the resource investments for different provinces.

Universal access to HIV treatment in developing countries: going beyond the misinterpretations of the 'cost-effectiveness' algorithm.

PubMed

Moatti, Jean Paul; Marlink, Richard; Luchini, Stephane; Kazatchkine, Michel

2008-07-01

Economic cost-effectiveness analysis (CEA) has been proposed as the appropriate tool to set priorities for resource allocation among available health interventions. Controversy remains about the way CEA should be used in the field of HIV/AIDS. This paper reviews the general literature in health economics and public economics about the use of CEA for priority setting in public health, in order better to inform current debates about resource allocation in the fight against HIV/AIDS. Theoretical and practical limitations of CEA do not raise major problems when it is applied to compare alternatives for treating the same medical condition or public health problem. Using CEA to set priorities among different health interventions by ranking them from the lowest to the highest values of their cost per life-year saved is appropriate only under the very restrictive and unrealistic assumptions that all interventions compared are discrete and finite alternatives that cannot vary in terms of size and scale. In order for CEA to inform resource allocation compared across programmes to fight the AIDS epidemic, a pragmatic interpretation of this economic approach, like that proposed by the Commission on Macroeconomics and Health, is better suited. Interventions, like a number of preventive strategies and first-line antiretroviral treatments for HIV, whose marginal costs per additional life-year saved are less than three times the gross domestic product per capita, should be considered cost-effective. Because of their empirical and theoretical limitations, results of CEA should only be one element in priority setting among interventions for HIV/AIDS, which should also be informed by explicit debates about societal and ethical preferences.

A Framework for Optimal Control Allocation with Structural Load Constraints

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc

2010-01-01

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Resource Allocation in High Schools. Final Report.

ERIC Educational Resources Information Center

Hartman, William T.

This study investigated the resource allocation process--how school administrators obtain the proper resources to operate their schools, distribute the available resources among the various school programs appropriately, and manage resources for effective educational results--in four high schools during the 1984-85 school year. Information was…

Preventing child pedestrian injury: pedestrian education or traffic calming?

PubMed

Roberts, I; Ashton, T; Dunn, R; Lee-Joe, T

1994-06-01

The traditional approach to the prevention of child pedestrian injuries in New Zealand is pedestrian education. However, none of the programs currently being implemented in New Zealand have ever been shown to reduce injury rates. The allocation of scarce resources to pedestrian education must therefore be questioned. In this paper we estimate the number of serious child pedestrian injuries which might be prevented if the resources allocated to pedestrian education were allocated instead to environmental approaches, in particular, to traffic calming. It is estimated that approximately 18 hospitalisations of child pedestrians could be prevented each year under this alternative resource allocation, disregarding any other benefits of traffic calming. These results emphasise the need to consider the potential sacrifices involved in the allocation of scarce resources to child pedestrian education.

Summary of Research 1997 Department of Systems Management.

DTIC Science & Technology

1999-01-01

formulation and execution; impacts of budget allocation , reallocation, and reduction; imple- mentation of Defense Resource Management Systems; and the...flexible structure that can be applied to a wide range of resource allocation problems. PUBLICATIONS: Dolk, D., Murphy, M., and Thomas, G...policies, procedures, and rationale in deter- mining recruiting resource allocation decisions. The methodology relies on a review of the literature

The Role of Temporal Context and Expectancy in Resource Allocation to and Perception of Rapid Serial Events

ERIC Educational Resources Information Center

Kranczioch, Cornelia; Dhinakaran, Janani

2013-01-01

The perception of target events presented in a rapid stream of non-targets is impaired for early target positions, but then gradually improves, a phenomenon known as attentional awakening. This phenomenon has been associated with better resource allocation. It is unclear though whether improved resource allocation and attentional awakening are a…

Budgeting and Resource Allocation at Princeton University. Report of a Demonstration Project.

ERIC Educational Resources Information Center

Benacerraf, Paul; And Others

This report summarizes the work done to date on a study of resource allocation in universities. This report specifically is concerned with budgeting and resource allocation at Princeton University. The document consists of 4 sections. The first section deals with the process of budgeting at Princeton as it has evolved over the last 4 years. After…

Strategic costs and preferences revelation in the allocation of resources for health care.

PubMed

Levaggi, Laura; Levaggi, Rosella

2010-09-01

This article examines the resources allocation process in the internal market for health care in an environment characterised by asymmetry of information. We analyse the strategic behaviour of the provider and show how, by misreporting its cost function and reservation utility, it might shift the allocation of resources away from the purchaser's objectives. Although the fundamental importance of equity, efficiency and risk aversion considerations which have been the traditional focus of the literature on allocation of resources should not be denied, this paper shows that contracts and internal markets are not neutral instruments and more research should be devoted to studying their effects.

Performance Evaluation Model for Application Layer Firewalls.

PubMed

Xuan, Shichang; Yang, Wu; Dong, Hui; Zhang, Jiangchuan

2016-01-01

Application layer firewalls protect the trusted area network against information security risks. However, firewall performance may affect user experience. Therefore, performance analysis plays a significant role in the evaluation of application layer firewalls. This paper presents an analytic model of the application layer firewall, based on a system analysis to evaluate the capability of the firewall. In order to enable users to improve the performance of the application layer firewall with limited resources, resource allocation was evaluated to obtain the optimal resource allocation scheme in terms of throughput, delay, and packet loss rate. The proposed model employs the Erlangian queuing model to analyze the performance parameters of the system with regard to the three layers (network, transport, and application layers). Then, the analysis results of all the layers are combined to obtain the overall system performance indicators. A discrete event simulation method was used to evaluate the proposed model. Finally, limited service desk resources were allocated to obtain the values of the performance indicators under different resource allocation scenarios in order to determine the optimal allocation scheme. Under limited resource allocation, this scheme enables users to maximize the performance of the application layer firewall.

Research on Evaluation of resource allocation efficiency of transportation system based on DEA

NASA Astrophysics Data System (ADS)

Zhang, Zhehui; Du, Linan

2017-06-01

In this paper, we select the time series data onto 1985-2015 years, construct the land (shoreline) resources, capital and labor as inputs. The index system of the output is freight volume and passenger volume, we use Quantitative analysis based on DEA method evaluated the resource allocation efficiency of railway, highway, water transport and civil aviation in China. Research shows that the resource allocation efficiency of various modes of transport has obvious difference, and the impact on scale efficiency is more significant. The most important two ways to optimize the allocation of resources to improve the efficiency of the combination of various modes of transport is promoting the co-ordination of various modes of transport and constructing integrated transportation system.

Priority setting and the ethics of resource allocation within VA healthcare facilities: results of a survey.

PubMed

Foglia, Mary Beth; Pearlman, Robert A; Bottrell, Melissa M; Altemose, Jane A; Fox, Ellen

2008-01-01

Setting priorities and the subsequent allocation of resources is a major ethical issue facing healthcare facilities, including the Veterans Health Administration (VHA), the largest integrated healthcare delivery network in the United States. Yet despite the importance of priority setting and its impact on those who receive and those who provide care, we know relatively little about how clinicians and managers view allocation processes within their facilities. The purpose of this secondary analysis of survey data was to characterize staff members' perceptions regarding the fairness of healthcare ethics practices related to resource allocation in Veterans Administration (VA) facilities. The specific aim of the study was to compare the responses of clinicians, clinician managers, and non-clinician managers with respect to these survey items. We utilized a paper and web-based survey and a cross-sectional design of VHA clinicians and managers. Our sample consisted of a purposive stratified sample of 109 managers and a stratified random sample of 269 clinicians employed 20 or more hours per week in one of four VA medical centers. The four medical centers were participating as field sites selected to test the logistics of administering and reporting results of the Integrated Ethics Staff Survey, an assessment tool aimed at characterizing a broad range of ethical practices within a healthcare organization. In general, clinicians were more critical than clinician managers or non-clinician managers of the institutions' allocation processes and of the impact of resource decisions on patient care. Clinicians commonly reported that they did not (a) understand their facility's decision-making processes, (b) receive explanations from management regarding the reasons behind important allocation decisions, or (b) perceive that they were influential in allocation decisions. In addition, clinicians and managers both perceived that education related to the ethics of resource allocation was insufficient and that their facilities could increase their effectiveness in identifying and resolving ethical problems related to resource allocation. How well a healthcare facility ensures fairness in the way it allocates its resources across programs and services depends on multiple factors, including awareness by decision makers that setting priorities and allocating resources is a moral enterprise (moral awareness), the availability of a consistent process that includes important stakeholder groups (procedural justice), and concurrence by stakeholders that decisions represent outcomes that fairly balance competing interests and have a positive net effect on the quality of care (distributive justice). In this study, clinicians and managers alike identified the need for improvement in healthcare ethics practices related to resource allocation.

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics

PubMed Central

Landa-Torres, Itziar; Manjarres, Diana; Bilbao, Sonia; Del Ser, Javier

2017-01-01

Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by devising three heuristic solvers aimed at efficiently scheduling tasks in robotic swarms, which collaborate together to accomplish a mission, and by presenting experimental results obtained over realistic scenarios in the underwater environment. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks and the relative execution order of such tasks within the schedule of certain robots. The obtained results reveal interesting differences in terms of Pareto optimality and spread between the algorithms considered in the benchmark, which are insightful for the selection of a proper task scheduler in real underwater campaigns. PMID:28375160

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics.

PubMed

Landa-Torres, Itziar; Manjarres, Diana; Bilbao, Sonia; Del Ser, Javier

2017-04-04

Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by devising three heuristic solvers aimed at efficiently scheduling tasks in robotic swarms, which collaborate together to accomplish a mission, and by presenting experimental results obtained over realistic scenarios in the underwater environment. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks and the relative execution order of such tasks within the schedule of certain robots. The obtained results reveal interesting differences in terms of Pareto optimality and spread between the algorithms considered in the benchmark, which are insightful for the selection of a proper task scheduler in real underwater campaigns.

Extended resource allocation index for link prediction of complex network

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-08-01

Recently, a number of similarity-based methods have been proposed to predict the missing links in complex network. Among these indices, the resource allocation index performs very well with lower time complexity. However, it ignores potential resources transferred by local paths between two endpoints. Motivated by the resource exchange taking places between endpoints, an extended resource allocation index is proposed. Empirical study on twelve real networks and three synthetic dynamic networks has shown that the index we proposed can achieve a good performance, compared with eight mainstream baselines.

On-Line Allocation Of Robot Resources To Task Plans

NASA Astrophysics Data System (ADS)

Lyons, Damian M.

1989-02-01

In this paper, I present an approach to representing plans that make on-line decisions about resource allocation. An on-line decision is the evaluation of a conditional expression involving sensory information as the plan is being executed. I use a plan representation called 7ZS10'1 1,12that has been especially designed for the domain of robot programming, and in particular, for the problem of on-line decisions. The resource allocation example is based on the robot assembly cell architecture outlined by Venkataraman and Lyons16. I begin by setting forth a definition of on-line decision making and some arguments as to why this form of decision making is important and useful. To set the context for the resource allocation example, I take some care in categorizing the types of on-line decision making and the approaches adopted by other workers so far. In particular, I justify a plan-based approach to the study of on-line decision making. From that, the focus shifts to one type of decision making: on-line allocation of robot resources to task plans. Robot resources are the physical manipulators (grippers, wrists, arms, feeders, etc) that are available to carry out the task. I formulate the assembly cell architecture of Venkataraman and Lyons16 as an R.S plan schema, and show how the on-line allocation specified in that architecture can be implemented. Finally, I show how considering the on-line allocation of logical resources, that is a physical resource plus some model information, can be used as a non-traditional approach to some problems in robot task planning.

Nephrologists' perspectives on waitlisting and allocation of deceased donor kidneys for transplant.

PubMed

Tong, Allison; Howard, Kirsten; Wong, Germaine; Cass, Alan; Jan, Stephen; Irving, Michelle; Craig, Jonathan C

2011-11-01

Deceased donor kidneys are a scarce resource and there is debate about how to maximize the benefit from each donated kidney while ensuring equity of access to transplants. Allocation of kidneys to waitlisted patients is determined by a computer algorithm, but the decision to waitlist patients or accept the kidneys offered is largely at the discretion of nephrologists. This study aims to elicit nephrologists' perspectives on waitlisting patients for kidney transplant and the allocation of deceased kidneys. We conducted semistructured face-to-face interviews with adult and pediatric nephrologists from 15 Australian nephrology or transplant centers. Transcripts were analyzed for descriptive and analytical themes. 25 nephrologists participated. 5 major themes on waitlisting and deceased donor kidney allocation were identified: patient advocacy (championing their own patients, empowering patients, giving hope, individualizing judgments, patient preferences, and limited autonomy), professional and moral integrity (transparency, avoiding value judgments, and eliminating bias), protecting center reputation (gatekeeping), achieving equity (uniformity, avoiding discrimination, and fairness for specific populations), and maximizing societal benefit (prioritizing best use of kidney, resource implications, favoring social contribution, and improving efficiency of the allocation process). In making individual patient assessments, estimates about outcomes for a patient had to be resolved with whether it was reasonable from a broader societal perspective. Nephrologists expressed their primary responsibility in terms of giving their own patients access to a transplant and upholding professional integrity by maintaining transparency and avoiding value judgments and bias. However, nephrologists perceived an obligation to protect their center's reputation through the selection of "good" patients, and this caused some frustration. Despite having personal preferences for optimizing the balance between societal benefit and equity, nephrologists did not want direct responsibility for ensuring societal benefit in clinical practice. Rather, they placed the onus on policy makers and the community to reconcile such tensions and advocate for societal benefit. Copyright © 2011 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Analysis of Online DBA Algorithm with Adaptive Sleep Cycle in WDM EPON

NASA Astrophysics Data System (ADS)

Pajčin, Bojan; Matavulj, Petar; Radivojević, Mirjana

2018-05-01

In order to manage Quality of Service (QoS) and energy efficiency in the optical access network, an online Dynamic Bandwidth Allocation (DBA) algorithm with adaptive sleep cycle is presented. This DBA algorithm has the ability to allocate an additional bandwidth to the end user within a single sleep cycle whose duration changes depending on the current buffers occupancy. The purpose of this DBA algorithm is to tune the duration of the sleep cycle depending on the network load in order to provide service to the end user without violating strict QoS requests in all network operating conditions.

Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation

NASA Astrophysics Data System (ADS)

Cheng, C. L.

2015-12-01

Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation Chung-Lien Cheng, Wen-Ping Tsai, Fi-John Chang* Department of Bioenvironmental Systems Engineering, National Taiwan University, Da-An District, Taipei 10617, Taiwan, ROC.Corresponding author: Fi-John Chang (changfj@ntu.edu.tw) AbstractIn Taiwan, the population growth and economic development has led to considerable and increasing demands for natural water resources in the last decades. Under such condition, water shortage problems have frequently occurred in northern Taiwan in recent years such that water is usually transferred from irrigation sectors to public sectors during drought periods. Facing the uneven spatial and temporal distribution of water resources and the problems of increasing water shortages, it is a primary and critical issue to simultaneously satisfy multiple water uses through adequate reservoir operations for sustainable water resources management. Therefore, we intend to build an intelligent reservoir operation system for the assessment of agricultural water resources management strategy in response to food security during drought periods. This study first uses the grey system to forecast the agricultural water demand during February and April for assessing future agricultural water demands. In the second part, we build an intelligent water resources system by using the non-dominated sorting genetic algorithm-II (NSGA-II), an optimization tool, for searching the water allocation series based on different water demand scenarios created from the first part to optimize the water supply operation for different water sectors. The results can be a reference guide for adequate agricultural water resources management during drought periods. Keywords: Non-dominated sorting genetic algorithm-II (NSGA-II); Grey System; Optimization; Agricultural Water Resources Management.

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

PubMed

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

A model of proto-object based saliency

PubMed Central

Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

2013-01-01

Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

Resource allocation processes at multilateral organizations working in global health.

PubMed

Chi, Y-Ling; Bump, Jesse B

2018-02-01

International institutions provide well over US$10 billion in development assistance for health (DAH) annually and between 1990 and 2014, DAH disbursements totaled $458 billion but how do they decide who gets what, and for what purpose? In this article, we explore how allocation decisions were made by the nine convening agencies of the Equitable Access Initiative. We provide clear, plain language descriptions of the complete process from resource mobilization to allocation for the nine multilateral agencies with prominent agendas in global health. Then, through a comparative analysis we illuminate the choices and strategies employed in the nine international institutions. We find that resource allocation in all reviewed institutions follow a similar pattern, which we categorized in a framework of five steps: strategy definition, resource mobilization, eligibility of countries, support type and funds allocation. All the reviewed institutions generate resource allocation decisions through well-structured and fairly complex processes. Variations in those processes seem to reflect differences in institutional principles and goals. However, these processes have serious shortcomings. Technical problems include inadequate flexibility to account for or meet country needs. Although aid effectiveness and value for money are commonly referenced, we find that neither performance nor impact is a major criterion for allocating resources. We found very little formal consideration of the incentives generated by allocation choices. Political issues include non-transparent influence on allocation processes by donors and bureaucrats, and the common practice of earmarking funds to bypass the normal allocation process entirely. Ethical deficiencies include low accountability and transparency at international institutions, and limited participation by affected citizens or their representatives. We find that recipient countries have low influence on allocation processes themselves, although within these processes they have some influence in relatively narrow areas. © The Author(s) 2018. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Assessing and Improving Performance: A Longitudinal Evaluation of Priority Setting and Resource Allocation in a Canadian Health Region

PubMed Central

Hall, William; Smith, Neale; Mitton, Craig; Urquhart, Bonnie; Bryan, Stirling

2018-01-01

Background: In order to meet the challenges presented by increasing demand and scarcity of resources, healthcare organizations are faced with difficult decisions related to resource allocation. Tools to facilitate evaluation and improvement of these processes could enable greater transparency and more optimal distribution of resources. Methods: The Resource Allocation Performance Assessment Tool (RAPAT) was implemented in a healthcare organization in British Columbia, Canada. Recommendations for improvement were delivered, and a follow up evaluation exercise was conducted to assess the trajectory of the organization’s priority setting and resource allocation (PSRA) process 2 years post the original evaluation. Results: Implementation of RAPAT in the pilot organization identified strengths and weaknesses of the organization’s PSRA process at the time of the original evaluation. Strengths included the use of criteria and evidence, an ability to reallocate resources, and the involvement of frontline staff in the process. Weaknesses included training, communication, and lack of program budgeting. Although the follow up revealed a regression from a more formal PSRA process, a legacy of explicit resource allocation was reported to be providing ongoing benefit for the organization. Conclusion: While past studies have taken a cross-sectional approach, this paper introduces the first longitudinal evaluation of PSRA in a healthcare organization. By including the strengths, weaknesses, and evolution of one organization’s journey, the authors’ intend that this paper will assist other healthcare leaders in meeting the challenges of allocating scarce resources. PMID:29626400

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

Resource Allocation and Seed Size Selection in Perennial Plants under Pollen Limitation.

PubMed

Huang, Qiaoqiao; Burd, Martin; Fan, Zhiwei

2017-09-01

Pollen limitation may affect resource allocation patterns in plants, but its role in the selection of seed size is not known. Using an evolutionarily stable strategy model of resource allocation in perennial iteroparous plants, we show that under density-independent population growth, pollen limitation (i.e., a reduction in ovule fertilization rate) should increase the optimal seed size. At any level of pollen limitation (including none), the optimal seed size maximizes the ratio of juvenile survival rate to the resource investment needed to produce one seed (including both ovule production and seed provisioning); that is, the optimum maximizes the fitness effect per unit cost. Seed investment may affect allocation to postbreeding adult survival. In our model, pollen limitation increases individual seed size but decreases overall reproductive allocation, so that pollen limitation should also increase the optimal allocation to postbreeding adult survival. Under density-dependent population growth, the optimal seed size is inversely proportional to ovule fertilization rate. However, pollen limitation does not affect the optimal allocation to postbreeding adult survival and ovule production. These results highlight the importance of allocation trade-offs in the effect pollen limitation has on the ecology and evolution of seed size and postbreeding adult survival in perennial plants.

Budgeting by Objectives--How Goals and Objectives, Operational Activities, and Resource Allocation Are Integrated in a Planning System. AIR 1984 Annual Forum Paper.

ERIC Educational Resources Information Center

Capoor, Madan

The Objective-Based Assessment, Planning, and Resource Allocation System (OAPRAS) that was developed and implemented at Middlesex County College is described. The integrated self-assessment planning and budgeting system was developed in 1981. The central purpose of OAPRAS was to link resource allocation decisions to the prioritized objectives that…

Personnel Resource Allocation Strategies in a Time of Fiscal Crisis: Case Study of Elementary Schools in a California District

ERIC Educational Resources Information Center

Sais, Melissa Marie

2013-01-01

The purpose of this study was to analyze human resource allocation data for all elementary schools in large urban school district to determine whether resources were allocated in ways in that research suggests can lead to improved student achievement. Data from all 46 elementary schools that participated in the study were compared to the…

Personalized recommendation via an improved NBI algorithm and user influence model in a Microblog network

NASA Astrophysics Data System (ADS)

Lian, Jie; Liu, Yun; Zhang, Zhen-jiang; Gui, Chang-ni

2013-10-01

Bipartite network based recommendations have attracted extensive attentions in recent years. Differing from traditional object-oriented recommendations, the recommendation in a Microblog network has two crucial differences. One is high authority users or one’s special friends usually play a very active role in tweet-oriented recommendation. The other is that the object in a Microblog network corresponds to a set of tweets on same topic instead of an actual and single entity, e.g. goods or movies in traditional networks. Thus repeat recommendations of the tweets in one’s collected topics are indispensable. Therefore, this paper improves network based inference (NBI) algorithm by original link matrix and link weight on resource allocation processes. This paper finally proposes the Microblog recommendation model based on the factors of improved network based inference and user influence model. Adjusting the weights of these two factors could generate the best recommendation results in algorithm accuracy and recommendation personalization.

Resource Allocation in Healthcare: Implications of Models of Medicine as a Profession

PubMed Central

Kluge, Eike-Henner W.

2007-01-01

For decades, the problem of how to allocate healthcare resources in a just and equitable fashion has been the subject of concerted discussion and analysis, yet the issue has stubbornly resisted resolution. This article suggests that a major reason for this is that the discussion has focused exclusively on the nature and status of the material resources, and that the nature and role of the medical profession have been entirely ignored. Because physicians are gatekeepers to healthcare resources, their role in allocation is central from a process perspective. This article identifies 3 distinct interpretations of the nature of medicine, shows how each mandates a different method of allocation, and argues that unless an appropriate model of medicine is developed that acknowledges the valid points contained in each of the 3 approaches, the allocation problem will remain unsolvable. PMID:17435657

A mathematical modeling approach to resource allocation for railroad-highway crossing safety upgrades.

PubMed

Konur, Dinçer; Golias, Mihalis M; Darks, Brandon

2013-03-01

State Departments of Transportation (S-DOT's) periodically allocate budget for safety upgrades at railroad-highway crossings. Efficient resource allocation is crucial for reducing accidents at railroad-highway crossings and increasing railroad as well as highway transportation safety. While a specific method is not restricted to S-DOT's, sorting type of procedures are recommended by the Federal Railroad Administration (FRA), United States Department of Transportation for the resource allocation problem. In this study, a generic mathematical model is proposed for the resource allocation problem for railroad-highway crossing safety upgrades. The proposed approach is compared to sorting based methods for safety upgrades of public at-grade railroad-highway crossings in Tennessee. The comparison shows that the proposed mathematical modeling approach is more efficient than sorting methods in reducing accidents and severity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimizing utilization of kidneys from deceased donors over 60 years: five-year outcomes after implementation of a combined clinical and histological allocation algorithm.

PubMed

Pierobon, Elisa Sefora; Sefora, Pierobon Elisa; Sandrini, Silvio; Silvio, Sandrini; De Fazio, Nicola; Nicola, De Fazio; Rossini, Giuseppe; Giuseppe, Rossini; Fontana, Iris; Iris, Fontana; Boschiero, Luigino; Luigino, Boschiero; Gropuzzo, Maria; Maria, Gropuzzo; Gotti, Eliana; Eliana, Gotti; Donati, Donato; Donato, Donati; Minetti, Enrico; Enrico, Minetti; Gandolfo, Maria Teresa; Teresa, Gandolfo Maria; Brunello, Anna; Anna, Brunello; Libetta, Carmelo; Carmelo, Libetta; Secchi, Antonio; Antonio, Secchi; Chiaramonte, Stefano; Stefano, Chiaramonte; Rigotti, Paolo; Paolo, Rigotti

2013-08-01

This 5 year observational multicentre study conducted in the Nord Italian Transplant programme area evaluated outcomes in patients receiving kidneys from donors over 60 years allocated according to a combined clinical and histological algorithm. Low-risk donors 60-69 years without risk factors were allocated to single kidney transplant (LR-SKT) based on clinical criteria. Biopsy was performed in donors over 70 years or 60-69 years with risk factors, allocated to Single (HR-SKT) or Dual kidney transplant (HR-DKT) according to the severity of histological damage. Forty HR-DKTs, 41 HR-SKTs and 234 LR-SKTs were evaluated. Baseline differences generally reflected stratification and allocation criteria. Patient and graft (death censored) survival were 90% and 92% for HR-DKT, 85% and 89% for HR-SKT, 88% and 87% for LR-SKT. The algorithm appeared user-friendly in daily practice and was safe and efficient, as demonstrated by satisfactory outcomes in all groups at 5 years. Clinical criteria performed well in low-risk donors. The excellent outcomes observed in DKTs call for fine-tuning of cut-off scores for allocation to DKT or SKT in high-risk patients. © 2013 Steunstichting ESOT. Published by John Wiley & Sons Ltd.

Study of network resource allocation based on market and game theoretic mechanism

NASA Astrophysics Data System (ADS)

Liu, Yingmei; Wang, Hongwei; Wang, Gang

2004-04-01

We work on the network resource allocation issue concerning network management system function based on market-oriented mechanism. The scheme is to model the telecommunication network resources as trading goods in which the various network components could be owned by different competitive, real-world entities. This is a multidisciplinary framework concentrating on the similarity between resource allocation in network environment and the market mechanism in economic theory. By taking an economic (market-based and game theoretic) approach in routing of communication network, we study the dynamic behavior under game-theoretic framework in allocating network resources. Based on the prior work of Gibney and Jennings, we apply concepts of utility and fitness to the market mechanism with an intention to close the gap between experiment environment and real world situation.

Ethical triage and scarce resource allocation during public health emergencies: tenets and procedures.

PubMed

Kuschner, Ware G; Pollard, John B; Ezeji-Okoye, Stephen C

2007-01-01

Public health emergencies may result in mass casualties and a surge in demand for hospital-based care. Healthcare standards may need to be altered to respond to an imbalance between demands for care and resources. Clinical decisions that involve triage and scarce resource allocation may present unique ethical challenges. To address these challenges, the authors detailed tenets and procedures to guide triage and scarce resource allocation during public health emergencies. The authors propose health care organizations deploy a Triage and Scarce Resource Allocation Team to over-see and guide ethically challenging clinical decision-making during a crisis period. The authors' goal is to help healthcare organizations and clinicians balance public health responsibilities and their duty to individual patients during emergencies in as equitable and humane a manner as possible.

Decentralization and equity of resource allocation: evidence from Colombia and Chile.

PubMed Central

Bossert, Thomas J.; Larrañaga, Osvaldo; Giedion, Ursula; Arbelaez, José Jesus; Bowser, Diana M.

2003-01-01

OBJECTIVE: To investigate the relation between decentralization and equity of resource allocation in Colombia and Chile. METHODS: The "decision space" approach and analysis of expenditures and utilization rates were used to provide a comparative analysis of decentralization of the health systems of Colombia and Chile. FINDINGS: Evidence from Colombia and Chile suggests that decentralization, under certain conditions and with some specific policy mechanisms, can improve equity of resource allocation. In these countries, equitable levels of per capita financial allocations at the municipal level were achieved through different forms of decentralization--the use of allocation formulae, adequate local funding choices and horizontal equity funds. Findings on equity of utilization of services were less consistent, but they did show that increased levels of funding were associated with increased utilization. This suggests that improved equity of funding over time might reduce inequities of service utilization. CONCLUSION: Decentralization can contribute to, or at least maintain, equitable allocation of health resources among municipalities of different incomes. PMID:12751417

Self-Regulated Reading in Adulthood

PubMed Central

Stine-Morrow, Elizabeth A. L.; Soederberg Miller, Lisa M.; Gagne, Danielle D.; Hertzog, Christopher

2008-01-01

Younger and older adults read a series of passages of three different genres for an immediate assessment of text memory (measured by recall and true-false questions). Word-by-word reading times were measured and decomposed into components reflecting resource allocation to particular linguistic processes using regression. Allocation to word and textbase processes showed some consistency across the three text types and was predictive of memory performance. Older adults allocated more time to word and textbase processes than the young did, but showed enhanced contextual facilitation. Structural equation modeling showed that greater resource allocation to word processes was required among readers with relatively low working memory spans and poorer verbal ability, and that greater resource allocation to textbase processes was engendered by higher verbal ability. Results are discussed in terms of a model of self-regulated language processing suggesting that older readers may compensate for processing deficiencies through greater reliance on discourse context and on increases in resource allocation that are enabled through growth in crystallized ability. PMID:18361662

Diffusion-based recommendation with trust relations on tripartite graphs

NASA Astrophysics Data System (ADS)

Wang, Ximeng; Liu, Yun; Zhang, Guangquan; Xiong, Fei; Lu, Jie

2017-08-01

The diffusion-based recommendation approach is a vital branch in recommender systems, which successfully applies physical dynamics to make recommendations for users on bipartite or tripartite graphs. Trust links indicate users’ social relations and can provide the benefit of reducing data sparsity. However, traditional diffusion-based algorithms only consider rating links when making recommendations. In this paper, the complementarity of users’ implicit and explicit trust is exploited, and a novel resource-allocation strategy is proposed, which integrates these two kinds of trust relations on tripartite graphs. Through empirical studies on three benchmark datasets, our proposed method obtains better performance than most of the benchmark algorithms in terms of accuracy, diversity and novelty. According to the experimental results, our method is an effective and reasonable way to integrate additional features into the diffusion-based recommendation approach.

Rectifying Social Inequalities in a Resource Allocation Task

PubMed Central

Elenbaas, Laura; Rizzo, Michael T.; Cooley, Shelby; Killen, Melanie

2016-01-01

To investigate whether children rectify social inequalities in a resource allocation task, participants (N = 185 African-American and European-American 5–6 year-olds and 10–11 year-olds) witnessed an inequality of school supplies between peers of different racial backgrounds. Assessments were conducted on how children judged the wrongfulness of the inequality, allocated new resources to racial ingroup and outgroup recipients, evaluated alternative allocation strategies, and reasoned about their decisions. Younger children showed ingroup favorability; their responses differed depending on whether they had witnessed their ingroup or an outgroup at a disadvantage. With age, children increasingly reasoned about the importance of equal access to school supplies and correcting past disparities. Older children judged the resource inequality negatively, allocated more resources to the disadvantaged group, and positively evaluated the actions of others who did the same, regardless of whether they had seen their racial ingroup or an outgroup at a disadvantage. Thus, balancing moral and social group concerns enabled individuals to rectify inequalities and ensure fair access to important resources regardless of racial group membership. PMID:27423813

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Eavesdropping-aware routing and spectrum allocation based on multi-flow virtual concatenation for confidential information service in elastic optical networks

NASA Astrophysics Data System (ADS)

Bai, Wei; Yang, Hui; Yu, Ao; Xiao, Hongyun; He, Linkuan; Feng, Lei; Zhang, Jie

2018-01-01

The leakage of confidential information is one of important issues in the network security area. Elastic Optical Networks (EON) as a promising technology in the optical transport network is under threat from eavesdropping attacks. It is a great demand to support confidential information service (CIS) and design efficient security strategy against the eavesdropping attacks. In this paper, we propose a solution to cope with the eavesdropping attacks in routing and spectrum allocation. Firstly, we introduce probability theory to describe eavesdropping issue and achieve awareness of eavesdropping attacks. Then we propose an eavesdropping-aware routing and spectrum allocation (ES-RSA) algorithm to guarantee information security. For further improving security and network performance, we employ multi-flow virtual concatenation (MFVC) and propose an eavesdropping-aware MFVC-based secure routing and spectrum allocation (MES-RSA) algorithm. The presented simulation results show that the proposed two RSA algorithms can both achieve greater security against the eavesdropping attacks and MES-RSA can also improve the network performance efficiently.

A cognitive gateway-based spectrum sharing method in downlink round robin scheduling of LTE system

NASA Astrophysics Data System (ADS)

Deng, Hongyu; Wu, Cheng; Wang, Yiming

2017-07-01

A key technique of LTE is how to allocate efficiently the resource of radio spectrum. Traditional Round Robin (RR) scheduling scheme may lead to too many resource residues when allocating resources. When the number of users in the current transmission time interval (TTI) is not the greatest common divisor of resource block groups (RBGs), and such a phenomenon lasts for a long time, the spectrum utilization would be greatly decreased. In this paper, a novel spectrum allocation scheme of cognitive gateway (CG) was proposed, in which the LTE spectrum utilization and CG’s throughput were greatly increased by allocating idle resource blocks in the shared TTI in LTE system to CG. Our simulation results show that the spectrum resource sharing method can improve LTE spectral utilization and increase the CG’s throughput as well as network use time.

Contrarian behavior in a complex adaptive system

NASA Astrophysics Data System (ADS)

Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

2013-01-01

Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

The Advantage of Standardisation as a Management Instrument in Companies

DTIC Science & Technology

2003-09-01

possible synergistic effects between different but related business units and allocate all kinds of resources in the best possible way. The management... allocating the necessary resources. This pragmatic approach corresponds to the "structure follows strategy thesis". Under the term strategy this thesis...implementation of the necessary arrangements in the functional areas as well as the allocation of existing resources. In this connection the demand for

Resource Allocation and Budgeting for the 1972-73 Mini-Schools of the Alum Rock Voucher Demonstration. Analysis of the Education Voucher Demonstration. A Working Note.

ERIC Educational Resources Information Center

Haggart, S. A.; Furry, W. S.

This Working Note documents the first year's events and outcomes in developing the budgeting system and resource allocation rules to support the Education Voucher Demonstration. The district now has systems for per pupil resource allocation and school/minischool cost center accounting. The basic voucher of $1,041 for grades 7-8, and $788 for…

Joint Rhythmic Movement Increases 4-Year-Old Children's Prosocial Sharing and Fairness Toward Peers.

PubMed

Rabinowitch, Tal-Chen; Meltzoff, Andrew N

2017-01-01

The allocation of resources to a peer partner is a prosocial act that is of fundamental importance. Joint rhythmic movement, such as occurs during musical interaction, can induce positive social experiences, which may play a role in developing and enhancing young children's prosocial skills. Here, we investigated whether joint rhythmic movement, free of musical context, increases 4-year-olds' sharing and sense of fairness in a resource allocation task involving peers. We developed a precise procedure for administering joint synchronous experience, joint asynchronous experience, and a baseline control involving no treatment. Then we tested how participants allocated resources between self and peer. We found an increase in the generous allocation of resources to peers following both synchronous and asynchronous movement compared to no treatment. At a more theoretical level, this result is considered in relation to previous work testing other aspects of child prosociality, for example, peer cooperation, which can be distinguished from judgments of fairness in resource allocation tasks. We draw a conceptual distinction between two types of prosocial behavior: resource allocation (an other-directed individual behavior) and cooperation (a goal-directed collaborative endeavor). Our results highlight how rhythmic interactions, which are prominent in joint musical engagements and synchronized activity, influence prosocial behavior between preschool peers.

Joint Rhythmic Movement Increases 4-Year-Old Children’s Prosocial Sharing and Fairness Toward Peers

PubMed Central

Rabinowitch, Tal-Chen; Meltzoff, Andrew N.

2017-01-01

The allocation of resources to a peer partner is a prosocial act that is of fundamental importance. Joint rhythmic movement, such as occurs during musical interaction, can induce positive social experiences, which may play a role in developing and enhancing young children’s prosocial skills. Here, we investigated whether joint rhythmic movement, free of musical context, increases 4-year-olds’ sharing and sense of fairness in a resource allocation task involving peers. We developed a precise procedure for administering joint synchronous experience, joint asynchronous experience, and a baseline control involving no treatment. Then we tested how participants allocated resources between self and peer. We found an increase in the generous allocation of resources to peers following both synchronous and asynchronous movement compared to no treatment. At a more theoretical level, this result is considered in relation to previous work testing other aspects of child prosociality, for example, peer cooperation, which can be distinguished from judgments of fairness in resource allocation tasks. We draw a conceptual distinction between two types of prosocial behavior: resource allocation (an other-directed individual behavior) and cooperation (a goal-directed collaborative endeavor). Our results highlight how rhythmic interactions, which are prominent in joint musical engagements and synchronized activity, influence prosocial behavior between preschool peers. PMID:28694786

Stochastic Optimization For Water Resources Allocation

NASA Astrophysics Data System (ADS)

Yamout, G.; Hatfield, K.

2003-12-01

For more than 40 years, water resources allocation problems have been addressed using deterministic mathematical optimization. When data uncertainties exist, these methods could lead to solutions that are sub-optimal or even infeasible. While optimization models have been proposed for water resources decision-making under uncertainty, no attempts have been made to address the uncertainties in water allocation problems in an integrated approach. This paper presents an Integrated Dynamic, Multi-stage, Feedback-controlled, Linear, Stochastic, and Distributed parameter optimization approach to solve a problem of water resources allocation. It attempts to capture (1) the conflict caused by competing objectives, (2) environmental degradation produced by resource consumption, and finally (3) the uncertainty and risk generated by the inherently random nature of state and decision parameters involved in such a problem. A theoretical system is defined throughout its different elements. These elements consisting mainly of water resource components and end-users are described in terms of quantity, quality, and present and future associated risks and uncertainties. Models are identified, modified, and interfaced together to constitute an integrated water allocation optimization framework. This effort is a novel approach to confront the water allocation optimization problem while accounting for uncertainties associated with all its elements; thus resulting in a solution that correctly reflects the physical problem in hand.

Atypical resource allocation may contribute to many aspects of autism

PubMed Central

Goldknopf, Emily J.

2013-01-01

Based on a review of the literature and on reports by people with autism, this paper suggests that atypical resource allocation is a factor that contributes to many aspects of autism spectrum conditions, including difficulties with language and social cognition, atypical sensory and attentional experiences, executive and motor challenges, and perceptual and conceptual strengths and weaknesses. Drawing upon resource theoretical approaches that suggest that perception, cognition, and action draw upon multiple pools of resources, the approach hypothesizes that compared with resources in typical cognition, resources in autism are narrowed or reduced, especially in people with strong sensory symptoms. In narrowed attention, resources are restricted to smaller areas and to fewer modalities, stages of processing, and cognitive processes than in typical cognition; narrowed resources may be more intense than in typical cognition. In reduced attentional capacity, overall resources are reduced; resources may be restricted to fewer modalities, stages of processing, and cognitive processes than in typical cognition, or the amount of resources allocated to each area or process may be reduced. Possible neural bases of the hypothesized atypical resource allocation, relations to other approaches, limitations, and tests of the hypotheses are discussed. PMID:24421760

Strategically Allocating Resources to Support Teaching and Learning

ERIC Educational Resources Information Center

Lynch, Matthew

2012-01-01

As the enduring economic recession forces state and local governments to cut education budgets, astute allocation of resources is becoming more important. The author analyses three basic categories of educational resources: money, human capital, and time before moving to a discussion of resources as a component of school reform. The author…

Ground data systems resource allocation process

NASA Technical Reports Server (NTRS)

Berner, Carol A.; Durham, Ralph; Reilly, Norman B.

1989-01-01

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Many-objective robust decision making for water allocation under climate change.

PubMed

Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

2017-12-31

Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

A distributed scheduling algorithm for heterogeneous real-time systems

NASA Technical Reports Server (NTRS)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

Discrete Resource Allocation in Visual Working Memory

ERIC Educational Resources Information Center

Barton, Brian; Ester, Edward F.; Awh, Edward

2009-01-01

Are resources in visual working memory allocated in a continuous or a discrete fashion? On one hand, flexible resource models suggest that capacity is determined by a central resource pool that can be flexibly divided such that items of greater complexity receive a larger share of resources. On the other hand, if capacity in working memory is…

Sustainability in health care by allocating resources effectively (SHARE) 3: examining how resource allocation decisions are made, implemented and evaluated in a local healthcare setting.

PubMed

Harris, Claire; Allen, Kelly; Waller, Cara; Brooke, Vanessa

2017-05-09

This is the third in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Leaders in a large Australian health service planned to establish an organisation-wide, systematic, integrated, evidence-based approach to disinvestment. In order to introduce new systems and processes for disinvestment into existing decision-making infrastructure, we aimed to understand where, how and by whom resource allocation decisions were made, implemented and evaluated. We also sought the knowledge and experience of staff regarding previous disinvestment activities. Structured interviews, workshops and document analysis were used to collect information from multiple sources in an environmental scan of decision-making systems and processes. Findings were synthesised using a theoretical framework. Sixty-eight respondents participated in interviews and workshops. Eight components in the process of resource allocation were identified: Governance, Administration, Stakeholder engagement, Resources, Decision-making, Implementation, Evaluation and, where appropriate, Reinvestment of savings. Elements of structure and practice for each component are described and a new framework was developed to capture the relationships between them. A range of decision-makers, decision-making settings, type and scope of decisions, criteria used, and strengths, weaknesses, barriers and enablers are outlined. The term 'disinvestment' was not used in health service decision-making. Previous projects that involved removal, reduction or restriction of current practices were driven by quality and safety issues, evidence-based practice or a need to find resource savings and not by initiatives where the primary aim was to disinvest. Measuring resource savings is difficult, in some situations impossible. Savings are often only theoretical as resources released may be utilised immediately by patients waiting for beds, clinic appointments or surgery. Decision-making systems and processes for resource allocation are more complex than assumed in previous studies. There is a wide range of decision-makers, settings, scope and type of decisions, and criteria used for allocating resources within a single institution. To our knowledge, this is the first paper to report this level of detail and to introduce eight components of the resource allocation process identified within a local health service.

A novel frame-level constant-distortion bit allocation for smooth H.264/AVC video quality

NASA Astrophysics Data System (ADS)

Liu, Li; Zhuang, Xinhua

2009-01-01

It is known that quality fluctuation has a major negative effect on visual perception. In previous work, we introduced a constant-distortion bit allocation method [1] for H.263+ encoder. However, the method in [1] can not be adapted to the newest H.264/AVC encoder directly as the well-known chicken-egg dilemma resulted from the rate-distortion optimization (RDO) decision process. To solve this problem, we propose a new two stage constant-distortion bit allocation (CDBA) algorithm with enhanced rate control for H.264/AVC encoder. In stage-1, the algorithm performs RD optimization process with a constant quantization QP. Based on prediction residual signals from stage-1 and target distortion for smooth video quality purpose, the frame-level bit target is allocated by using a close-form approximations of ratedistortion relationship similar to [1], and a fast stage-2 encoding process is performed with enhanced basic unit rate control. Experimental results show that, compared with original rate control algorithm provided by H.264/AVC reference software JM12.1, the proposed constant-distortion frame-level bit allocation scheme reduces quality fluctuation and delivers much smoother PSNR on all testing sequences.

The international environment UNISPACE '82 and the ITU: A relationship between orbit-spectrum resource allocation and orbital debris

NASA Technical Reports Server (NTRS)

Olmstead, D.

1985-01-01

The 1985 Space WARC will examine and potentially modify the current geostationary orbit spectrum resource allocation methodology. Discussions in this international political environment could likely associate the geostationary orbital debris issue with the politicized issue of orbit spectrum allocation.

On the Allocation of Resources for Secondary Schools

ERIC Educational Resources Information Center

Haelermans, Carla; De Witte, Kristof; Blank, Jos L. T.

2012-01-01

This paper studies the optimal allocation of resources--in terms of school management, teachers, supporting employees and materials--in secondary schools. We use a flexible budget constrained output distance function model to estimate both technical and allocative efficiency scores for 448 Dutch secondary schools between 2002 and 2007. The results…

Accelerating Dust Storm Simulation by Balancing Task Allocation in Parallel Computing Environment

NASA Astrophysics Data System (ADS)

Gui, Z.; Yang, C.; XIA, J.; Huang, Q.; YU, M.

2013-12-01

Dust storm has serious negative impacts on environment, human health, and assets. The continuing global climate change has increased the frequency and intensity of dust storm in the past decades. To better understand and predict the distribution, intensity and structure of dust storm, a series of dust storm models have been developed, such as Dust Regional Atmospheric Model (DREAM), the NMM meteorological module (NMM-dust) and Chinese Unified Atmospheric Chemistry Environment for Dust (CUACE/Dust). The developments and applications of these models have contributed significantly to both scientific research and our daily life. However, dust storm simulation is a data and computing intensive process. Normally, a simulation for a single dust storm event may take several days or hours to run. It seriously impacts the timeliness of prediction and potential applications. To speed up the process, high performance computing is widely adopted. By partitioning a large study area into small subdomains according to their geographic location and executing them on different computing nodes in a parallel fashion, the computing performance can be significantly improved. Since spatiotemporal correlations exist in the geophysical process of dust storm simulation, each subdomain allocated to a node need to communicate with other geographically adjacent subdomains to exchange data. Inappropriate allocations may introduce imbalance task loads and unnecessary communications among computing nodes. Therefore, task allocation method is the key factor, which may impact the feasibility of the paralleling. The allocation algorithm needs to carefully leverage the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire system. This presentation introduces two algorithms for such allocation and compares them with evenly distributed allocation method. Specifically, 1) In order to get optimized solutions, a quadratic programming based modeling method is proposed. This algorithm performs well with small amount of computing tasks. However, its efficiency decreases significantly as the subdomain number and computing node number increase. 2) To compensate performance decreasing for large scale tasks, a K-Means clustering based algorithm is introduced. Instead of dedicating to get optimized solutions, this method can get relatively good feasible solutions within acceptable time. However, it may introduce imbalance communication for nodes or node-isolated subdomains. This research shows both two algorithms have their own strength and weakness for task allocation. A combination of the two algorithms is under study to obtain a better performance. Keywords: Scheduling; Parallel Computing; Load Balance; Optimization; Cost Model

The use of an integrated variable fuzzy sets in water resources management

NASA Astrophysics Data System (ADS)

Qiu, Qingtai; Liu, Jia; Li, Chuanzhe; Yu, Xinzhe; Wang, Yang

2018-06-01

Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

Location-allocation models and new solution methodologies in telecommunication networks

NASA Astrophysics Data System (ADS)

Dinu, S.; Ciucur, V.

2016-08-01

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

Enhancements and Algorithms for Avionic Information Processing System Design Methodology.

DTIC Science & Technology

1982-06-16

programming algorithm is enhanced by incorporating task precedence constraints and hardware failures. Stochastic network methods are used to analyze...allocations in the presence of random fluctuations. Graph theoretic methods are used to analyze hardware designs, and new designs are constructed with...There, spatial dynamic programming (SDP) was used to solve a static, deterministic software allocation problem. Under the current contract the SDP

Congestion Pricing for Aircraft Pushback Slot Allocation.

PubMed

Liu, Lihua; Zhang, Yaping; Liu, Lan; Xing, Zhiwei

2017-01-01

In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.

Congestion Pricing for Aircraft Pushback Slot Allocation

PubMed Central

Zhang, Yaping

2017-01-01

In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the “external cost of surface congestion” is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm. PMID:28114429

Collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation

NASA Astrophysics Data System (ADS)

Yang, Shangwen; Guo, Baohua; Xiao, Xuefei; Gao, Haichao

2018-01-01

To allocate the en-routes and slots to the flights with collaborative decision making, a collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation was proposed. Evaluation indexes include flight delay costs, delay time and the number of turning points. Analytic hierarchy process is applied to determining index weights. Remark set for current two flights not yet obtained the en-route and slot in flight schedule is established. Then, fuzzy comprehensive evaluation is performed, and the en-route and slot for the current two flights are determined. Continue selecting the flight not yet obtained an en-route and a slot in flight schedule. Perform fuzzy comprehensive evaluation until all flights have obtained the en-routes and slots. MatlabR2007b was applied to numerical test based on the simulated data of a civil en-route. Test results show that, compared with the traditional strategy of first come first service, the algorithm gains better effect. The effectiveness of the algorithm was verified.

A Two-Phase Model of Resource Allocation in Visual Working Memory

ERIC Educational Resources Information Center

Ye, Chaoxiong; Hu, Zhonghua; Li, Hong; Ristaniemi, Tapani; Liu, Qiang; Liu, Taosheng

2017-01-01

Two broad theories of visual working memory (VWM) storage have emerged from current research, a discrete slot-based theory and a continuous resource theory. However, neither the discrete slot-based theory or continuous resource theory clearly stipulates how the mental commodity for VWM (discrete slot or continuous resource) is allocated.…

Resource Allocation Procedure at Queensland University: A Dynamic Modelling Project.

ERIC Educational Resources Information Center

Galbraith, Peter L.; Carss, Brian W.

A structural reorganization of the University of Queensland, Australia, was undertaken to promote efficient resource management, and a resource allocation model was developed to aid in policy evaluation and planning. The operation of the restructured system was based on creating five resource groups to manage the distribution of academic resources…

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

Simple versus composite indicators of socioeconomic status in resource allocation formulae: the case of the district resource allocation formula in Malawi

PubMed Central

2010-01-01

Background The district resource allocation formula in Malawi was recently reviewed to include stunting as a proxy measure of socioeconomic status. In many countries where the concept of need has been incorporated in resource allocation, composite indicators of socioeconomic status have been used. In the Malawi case, it is important to ascertain whether there are differences between using single variable or composite indicators of socioeconomic status in allocations made to districts, holding all other factors in the resource allocation formula constant. Methods Principal components analysis was used to calculate asset indices for all districts from variables that capture living standards using data from the Malawi Multiple Indicator Cluster Survey 2006. These were normalized and used to weight district populations. District proportions of national population weighted by both the simple and composite indicators were then calculated for all districts and compared. District allocations were also calculated using the two approaches and compared. Results The two types of indicators are highly correlated, with a spearman rank correlation coefficient of 0.97 at the 1% level of significance. For 21 out of the 26 districts included in the study, proportions of national population weighted by the simple indicator are higher by an average of 0.6 percentage points. For the remaining 5 districts, district proportions of national population weighted by the composite indicator are higher by an average of 2 percentage points. Though the average percentage point differences are low and the actual allocations using both approaches highly correlated (ρ of 0.96), differences in actual allocations exceed 10% for 8 districts and have an average of 4.2% for the remaining 17. For 21 districts allocations based on the single variable indicator are higher. Conclusions Variations in district allocations made using either the simple or composite indicators of socioeconomic status are not statistically different to recommend one over the other. However, the single variable indicator is favourable for its ease of computation. PMID:20053274

Healthcare resource allocation decisions affecting uninsured services

PubMed Central

Harrison, Krista Lyn; Taylor, Holly A.

2017-01-01

Purpose Using the example of community access programs (CAPs), the purpose of this paper is to describe resource allocation and policy decisions related to providing health services for the uninsured in the USA and the organizational values affecting these decisions. Design/methodology/approach The study used comparative case study methodology at two geographically diverse sites. Researchers collected data from program documents, meeting observations, and interviews with program stakeholders. Findings Five resource allocation or policy decisions relevant to providing healthcare services were described at each site across three categories: designing the health plan, reacting to funding changes, and revising policies. Organizational values of access to care and stewardship most frequently affected resource allocation and policy decisions, while economic and political pressures affect the relative prioritization of values. Research limitations/implications Small sample size, the potential for social desirability or recall bias, and the exclusion of provider, member or community perspectives beyond those represented among participating board members. Practical implications Program directors or researchers can use this study to assess the extent to which resource allocation and policy decisions align with organizational values and mission statements. Social implications The description of how healthcare decisions are actually made can be matched with literature that describes how healthcare resource decisions ought to be made, in order to provide a normative grounding for future decisions. Originality/value This study addresses a gap in literature regarding how CAPs actually make resource allocation decisions that affect access to healthcare services. PMID:27934550

Scarcity, Conflict, and Equity in Allocating Public Recreation Resources.

ERIC Educational Resources Information Center

Shelby, Bo; Danley, Mark

The conflict between the interests of commercial outfitters and private boaters in the use of whitewater rivers is examined. A discussion is presented on the literature on scarcity, allocation, and conflict among groups. These concepts are applied to the allocation of public resources on whitewater rivers. The conflicting interest groups are…

77 FR 42749 - Proposed Change in State Title V Maternal and Child Health Block Grant Allocations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-20

... Change in State Title V Maternal and Child Health Block Grant Allocations AGENCY: Health Resources and... the State Title V Maternal and Child Health (MCH) Block Grant allocations. Through the Health Resources and Services Administration's Maternal and Child Health Bureau (MCHB), Title V MCH Block Grant...

Equity in the allocation of public sector financial resources in low- and middle-income countries: a systematic literature review.

PubMed

Anselmi, Laura; Lagarde, Mylene; Hanson, Kara

2015-05-01

This review aims to identify, assess and analyse the evidence on equity in the distribution of public health sector expenditure in low- and middle-income countries. Four bibliographic databases and five websites were searched to identify quantitative studies examining equity in the distribution of public health funding in individual countries or groups of countries. Two different types of studies were identified: benefit incidence analysis (BIA) and resource allocation comparison (RAC) studies. Quality appraisal and data synthesis were tailored to each study type to reflect differences in the methods used and in the information provided. We identified 39 studies focusing on African, Asian and Latin American countries. Of these, 31 were BIA studies that described the distribution, typically across socio-economic status, of individual monetary benefit derived from service utilization. The remaining eight were RAC studies that compared the actual expenditure across geographic areas to an ideal need-based distribution. Overall, the quality of the evidence from both types of study was relatively weak. Looking across studies, the evidence confirms that resource allocation formulae can enhance equity in resource allocation across geographic areas and that the poor benefits proportionally more from primary health care than from hospital expenditure. The lack of information on the distribution of benefit from utilization in RAC studies and on the countries' approaches to resource allocation in BIA studies prevents further policy analysis. Additional research that relates the type of resource allocation mechanism to service provision and to the benefit distribution is required for a better understanding of equity-enhancing resource allocation policies. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.

Sustainability in health care by allocating resources effectively (SHARE) 4: exploring opportunities and methods for consumer engagement in resource allocation in a local healthcare setting.

PubMed

Harris, Claire; Ko, Henry; Waller, Cara; Sloss, Pamela; Williams, Pamela

2017-05-05

This is the fourth in a series of papers reporting a program of Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. Healthcare decision-makers have sought to improve the effectiveness and efficiency of services through removal or restriction of practices that are unsafe or of little benefit, often referred to as 'disinvestment'. A systematic, integrated, evidence-based program for disinvestment was being established within a large Australian health service network. Consumer engagement was acknowledged as integral to this process. This paper reports the process of developing a model to integrate consumer views and preferences into an organisation-wide approach to resource allocation. A literature search was conducted and interviews and workshops were undertaken with health service consumers and staff. Findings were drafted into a model for consumer engagement in resource allocation which was workshopped and refined. Although consumer engagement is increasingly becoming a requirement of publicly-funded health services and documented in standards and policies, participation in organisational decision-making is not widespread. Several consistent messages for consumer engagement in this context emerged from the literature and consumer responses. Opportunities, settings and activities for consumer engagement through communication, consultation and participation were identified within the resource allocation process. Sources of information regarding consumer values and perspectives in publications and locally-collected data, and methods to use them in health service decision-making, were identified. A model bringing these elements together was developed. The proposed model presents potential opportunities and activities for consumer engagement in the context of resource allocation.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

Factors that influence case managers' resource allocation decisions in pediatric home care: an ethnographic study.

PubMed

Fraser, Kimberly D; Estabrooks, Carole; Allen, Marion; Strang, Vicki

2009-03-01

Case managers make decisions that directly affect the amount and type of services home care clients receive and subsequently affect the overall available health care resources of home care programs. A recent systematic review of the literature identified significant knowledge gaps with respect to resource allocation decision-making in home care. Using Spradley's methodology, we designed an ethnographic study of a children's home care program in Western Canada. The sample included 11 case managers and program leaders. Data sources included interviews, card sorts, and participant observation over a 5-month period. Data analyses included open coding, domain, taxonomic, and componential analysis. One of the key findings was a taxonomy of factors that influence case manager resource allocation decisions. The factors were grouped into one of four main categories: system-related, home care program-related, family related, or client-related. Family related factors have not been previously reported as influencing case manager resource allocation decision-making and nor has the team's role been reported as an influencing factor. The findings of this study are examined in light of Daniels and Sabin's Accountability for Reasonableness framework, which may be useful for future knowledge development about micro-level resource allocation theory.

Mathematical programming for the efficient allocation of health care resources.

PubMed

Stinnett, A A; Paltiel, A D

1996-10-01

Previous discussions of methods for the efficient allocation of health care resources subject to a budget constraint have relied on unnecessarily restrictive assumptions. This paper makes use of established optimization techniques to demonstrate that a general mathematical programming framework can accommodate much more complex information regarding returns to scale, partial and complete indivisibility and program interdependence. Methods are also presented for incorporating ethical constraints into the resource allocation process, including explicit identification of the cost of equity.

Assessing and Improving Performance: A Longitudinal Evaluation of Priority Setting and Resource Allocation in a Canadian Health Region.

PubMed

Hall, William; Smith, Neale; Mitton, Craig; Urquhart, Bonnie; Bryan, Stirling

2017-08-22

In order to meet the challenges presented by increasing demand and scarcity of resources, healthcare organizations are faced with difficult decisions related to resource allocation. Tools to facilitate evaluation and improvement of these processes could enable greater transparency and more optimal distribution of resources. The Resource Allocation Performance Assessment Tool (RAPAT) was implemented in a healthcare organization in British Columbia, Canada. Recommendations for improvement were delivered, and a follow up evaluation exercise was conducted to assess the trajectory of the organization's priority setting and resource allocation (PSRA) process 2 years post the original evaluation. Implementation of RAPAT in the pilot organization identified strengths and weaknesses of the organization's PSRA process at the time of the original evaluation. Strengths included the use of criteria and evidence, an ability to reallocate resources, and the involvement of frontline staff in the process. Weaknesses included training, communication, and lack of program budgeting. Although the follow up revealed a regression from a more formal PSRA process, a legacy of explicit resource allocation was reported to be providing ongoing benefit for the organization. While past studies have taken a cross-sectional approach, this paper introduces the first longitudinal evaluation of PSRA in a healthcare organization. By including the strengths, weaknesses, and evolution of one organization's journey, the authors' intend that this paper will assist other healthcare leaders in meeting the challenges of allocating scarce resources. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Ethical considerations in resource allocation in a cochlear implant program.

PubMed

Westerberg, Brian D; Pijl, Sipke; McDonald, Michael

2008-04-01

To review processes of resource allocation and the ethical considerations relevant to the fair allocation of a limited number of cochlear implants to increasing numbers of potential recipients. Review of relevant considerations. Tertiary referral hospital. Editorial discussion of the ethical issues of resource allocation. Heterogeneity of audiometric thresholds, self-reported disability of hearing loss, age of the potential cochlear implant recipient, cost-effectiveness, access to resources, compliance with follow-up, social support available to the recipient, social consequences of hearing impairment, and other recipient-related factors. In a publicly funded health care system, there will always be a need for decision-making processes for allocation of finite fiscal resources. All candidates for cochlear implantation deserve fair consideration. However, they are a heterogeneous group in terms of needs and expected outcomes consisting of traditional and marginal candidates, with a wide range of benefit from acoustic amplification. We argue that implant programs should thoughtfully prioritize treatment on the basis of need and potential benefit. We reject queuing on the basis of "first-come, first-served" or on the basis of perceived social worth.

What is so important about completing lives? A critique of the modified youngest first principle of scarce resource allocation.

PubMed

Gamlund, Espen

2016-04-01

Ruth Tallman has recently offered a defense of the modified youngest first principle of scarce resource allocation [1]. According to Tallman, this principle calls for prioritizing adolescents and young adults between 15-40 years of age. In this article, I argue that Tallman's defense of the modified youngest first principle is vulnerable to important objections, and that it is thus unsuitable as a basis for allocating resources. Moreover, Tallman makes claims about the badness of death for individuals at different ages, but she lacks an account of the loss involved in dying to support her claims. To fill this gap in Tallman's account, I propose a view on the badness of death that I call 'Deprivationism'. I argue that this view explains why death is bad for those who die, and that it has some advantages over Tallman's complete lives view in the context of scarce resource allocation. Finally, I consider some objections to the relevance of Deprivationism to resource allocation, and offer my responses.

Resource allocation and compensation during development in holometabolous insects.

PubMed

Nestel, David; Papadopoulos, Nikos T; Pascacio-Villafán, Carlos; Righini, Nicoletta; Altuzar-Molina, Alma R; Aluja, Martín

2016-12-01

We provide an extensive review on current knowledge and future research paths on the topic of resource allocation and compensation during development in holometabolous insects, emphasizing the role of resource management during development, and how compensatory mechanisms may be acting to remediate nutritional deficiencies carried over from earlier stages of development. We first review resource allocation in "open" and "closed" developmental stages and then move on to the topic of modelling resource allocation and its trade-offs. In doing so, we review novel methodological developments such as response-surface methods and mixture experiments as well as nutritional geometry. We also dwell on the fascinating topic of compensatory physiology and behavior. We finish by discussing future research paths, among them the emerging field of nutrigenomics and gut microbiome, which will shed light into the yet poorly understood role of the symbiotic microbiota in nutrient compensation or assimilation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Arithmetic and algebraic problem solving and resource allocation: the distinct impact of fluid and numerical intelligence.

PubMed

Dix, Annika; van der Meer, Elke

2015-04-01

This study investigates cognitive resource allocation dependent on fluid and numerical intelligence in arithmetic/algebraic tasks varying in difficulty. Sixty-six 11th grade students participated in a mathematical verification paradigm, while pupil dilation as a measure of resource allocation was collected. Students with high fluid intelligence solved the tasks faster and more accurately than those with average fluid intelligence, as did students with high compared to average numerical intelligence. However, fluid intelligence sped up response times only in students with average but not high numerical intelligence. Further, high fluid but not numerical intelligence led to greater task-related pupil dilation. We assume that fluid intelligence serves as a domain-general resource that helps to tackle problems for which domain-specific knowledge (numerical intelligence) is missing. The allocation of this resource can be measured by pupil dilation. Copyright © 2014 Society for Psychophysiological Research.

Perceptions and Attitudes of Health Professionals in Kenya on National Health Care Resource Allocation Mechanisms: A Structural Equation Modeling

PubMed Central

Owili, Patrick Opiyo; Hsu, Yi-Hsin Elsa; Chern, Jin-Yuan; Chiu, Chiung-Hsuan Megan; Wang, Bill; Huang, Kuo-Cherh; Muga, Miriam Adoyo

2015-01-01

Background Health care resource allocation is key towards attaining equity in the health system. However, health professionals’ perceived impact and attitude towards health care resource allocation in Sub-Saharan Africa is unknown; furthermore, they occupy a position which makes them notice the impact of different policies in their health system. This study explored perceptions and attitudes of health professionals in Kenya on health care resource allocation mechanism. Method We conducted a survey of a representative sample of 341 health professionals in Moi Teaching and Referral Hospital from February to April 2012, consisting of over 3000 employees. We assessed health professionals’ perceived impact and attitudes on health care resource allocation mechanism in Kenya. We used structural equation modeling and applied a Confirmatory Factor Analysis using Robust Maximum Likelihood estimation procedure to test the hypothesized model. Results We found that the allocation mechanism was negatively associated with their perceived positive impact (-1.04, p < .001), health professionals’ satisfaction (-0.24, p < .01), and professionals’ attitudes (-1.55, p < .001) while it was positively associated with perceived negative impact (1.14, p < .001). Perceived positive impact of the allocation mechanism was negatively associated with their overall satisfaction (-0.08) and attitude (-0.98) at p < .001, respectively. Furthermore, overall satisfaction was negatively associated with attitude (-1.10, p <.001). On the other hand, perceived negative impact of the allocation was positively associated with overall satisfaction (0.29, p <.001) but was not associated with attitude. Conclusion The result suggests that health care resource allocation mechanism has a negative effect towards perceptions, attitudes and overall satisfaction of health professionals who are at the frontline in health care. These findings can serve as a crucial reference for policymakers as the Kenyan health system move towards devolving the system of governance. PMID:26039053

SDN based millimetre wave radio over fiber (RoF) network

NASA Astrophysics Data System (ADS)

Amate, Ahmed; Milosavljevic, Milos; Kourtessis, Pandelis; Robinson, Matthew; Senior, John M.

2015-01-01

This paper introduces software-defined, millimeter Wave (mm-Wave) networks with Radio over Fiber (RoF) for the delivery of gigabit connectivity required to develop fifth generation (5G) mobile. This network will enable an effective open access system allowing providers to manage and lease the infrastructure to service providers through unbundling new business models. Exploiting the inherited benefits of RoF, complete base station functionalities are centralized at the edges of the metro and aggregation network, leaving remote radio heads (RRHs) with only tunable filtering and amplification. A Software Defined Network (SDN) Central Controller (SCC) is responsible for managing the resource across several mm-Wave Radio Access Networks (RANs) providing a global view of the several network segments. This ensures flexible resource allocation for reduced overall latency and increased throughput. The SDN based mm-Wave RAN also allows for inter edge node communication. Therefore, certain packets can be routed between different RANs supported by the same edge node, reducing latency. System level simulations of the complete network have shown significant improvement of the overall throughput and SINR for wireless users by providing effective resource allocation and coordination among interfering cells. A new Coordinated Multipoint (CoMP) algorithm exploiting the benefits of the SCC global network view for reduced delay in control message exchange is presented, accounting for a minimum packet delay and limited Channel State Information (CSI) in a Long Term Evolution-Advanced (LTE-A), Cloud RAN (CRAN) configuration. The algorithm does not require detailed CSI feedback from UEs but it rather considers UE location (determined by the eNB) as the required parameter. UE throughput in the target sector is represented using a Cumulative Distributive Function (CDF). The drawn characteristics suggest that there is a significant 60% improvement in UE cell edge throughput following the application, in the coordinating cells, of the new CoMP algorithm. Results also show a further improvement of 36% in cell edge UE throughput when eNBs are centralized in a CRAN backhaul architecture. The SINR distribution of UEs in the cooperating cells has also been evaluated using a box plot. As expected, UEs with CoMP perform better demonstrating an increase of over 2 dB at the median between the transmission scenarios.

Criteria-Based Resource Allocation: A Tool to Improve Public Health Impact.

PubMed

Graham, J Ross; Mackie, Christopher

2016-01-01

Resource allocation in local public health (LPH) has been reported as a significant challenge for practitioners and a Public Health Services and Systems Research priority. Ensuring available resources have maximum impact on community health and maintaining public confidence in the resource allocation process are key challenges. A popular strategy in health care settings to address these challenges is Program Budgeting and Marginal Analysis (PBMA). This case study used PBMA in an LPH setting to examine its appropriateness and utility. The criteria-based resource allocation process PBMA was implemented to guide the development of annual organizational budget in an attempt to maximize the impact of agency resources. Senior leaders and managers were surveyed postimplementation regarding process facilitators, challenges, and successes. Canada's largest autonomous LPH agency. PBMA was used to shift 3.4% of the agency budget from lower-impact areas (through 34 specific disinvestments) to higher-impact areas (26 specific reinvestments). Senior leaders and managers validated the process as a useful approach for improving the public health impact of agency resources. However, they also reported the process may have decreased frontline staff confidence in senior leadership. In this case study, PBMA was used successfully to reallocate a sizable portion of an LPH agency's budget toward higher-impact activities. PBMA warrants further study as a tool to support optimal resource allocation in LPH settings.

Allocation of health resources according to the type and size of Iranian governmental hospitals.

PubMed

Hassani, Sa; Abolhallaje, M; Inanlo, S; Hosseini, H; Pourmohammadi, K; Bastani, P; Ramezanian, M; Marnani, A Barati

2013-01-01

Due to consuming about 50%-80% of health resources, hospitals are the greatest and costly operational units in Iranian Health system. so allocation of resources specially human and space resources as the most expensive ones is really important for further controlling of costs, analysis of costs and making suitable policies for increasing the profitability and allocation of resources and improvement of quality. This paper intends to describe and analyze any allocation of resources in 530 university hospitals in Iran. The final goal of this research is to provide a data bank according which there is a basis for more scientific budget allocation of state's hospitals from the size and type of application points of view. The relevant index of person to bed was 2.04 for human resources. All hospitals more than 300 beds are located in benefiting areas from which 17 cases are educational and 2 cases are therapeutic. This is necessary to mention that the rate of management group forces to total personnel at deprived areas is about 2.5% more than benefiting areas. Because 60-80% of hospital costs are applied for human forces, all managers of hospitals are obliged to revise their policies in attraction and employment of human force in order to benefit from such a valuable resource and prevent from expensive costs. So any employment of personnel should be based upon real needs of hospital.

Optimal Resource Allocation under Fair QoS in Multi-tier Server Systems

NASA Astrophysics Data System (ADS)

Akai, Hirokazu; Ushio, Toshimitsu; Hayashi, Naoki

Recent development of network technology realizes multi-tier server systems, where several tiers perform functionally different processing requested by clients. It is an important issue to allocate resources of the systems to clients dynamically based on their current requests. On the other hand, Q-RAM has been proposed for resource allocation in real-time systems. In the server systems, it is important that execution results of all applications requested by clients are the same QoS(quality of service) level. In this paper, we extend Q-RAM to multi-tier server systems and propose a method for optimal resource allocation with fairness of the QoS levels of clients’ requests. We also consider an assignment problem of physical machines to be sleep in each tier sothat the energy consumption is minimized.

Children Rectify Inequalities for Disadvantaged Groups

PubMed Central

Elenbaas, Laura; Killen, Melanie

2016-01-01

Children’s decisions regarding the allocation of societal resources in the context of preexisting inequalities were investigated. African-American and European-American children ages 5–6 years (n = 91) and 10–11 years (n = 94) judged the acceptability of a medical resource inequality on the basis of race, allocated medical supplies, evaluated different resource allocation strategies, and completed a measure of status awareness based on race. With age, children were increasingly aware of wealth status disparities between African-Americans and European-Americans, and judged a medical resource inequality between groups more negatively. Further, with age, children rectified the resource inequality over perpetuating it, but only when African-American children were disadvantaged. With age, children also referenced rights when reasoning about their judgments concerning the disadvantaged African-American group. When European-American children were disadvantaged, children did not systematically allocate more resources to one group over another. The results are discussed in terms of social inequalities, disadvantaged status, moral judgments, and intergroup attitudes. PMID:27455190

Flexibility of resource allocation in a hermaphroditic-gynomonoecious herb through deployment of female and male resources in perfect flowers.

PubMed

Mamut, Jannathan; Xiong, Ying-Ze; Tan, Dun-Yan; Huang, Shuang-Quan

2017-03-01

It has been hypothesized that two flower types permit flexible allocation of resources to female and male functions, yet empirical evidence for the sex-allocation hypothesis remains scarce in gynomonoecious species. To characterize resource allocation to pistillate and perfect flowers and allocation of perfect flowers between gynomonoecious and hermaphroditic individuals, we examined the flexibility and whether female-biased allocation increases with plant size in the hermaphroditic-gynomonoecious herb Eremurus anisopterus . Frequency of gynomonoecious individuals, flower production, and plant size were investigated in different populations. Floral allocation was compared among the three flower types of E. anisopterus . Frequency of gynomonoecious plants varied from 2-17% in nine populations. Only larger plants produced female flowers at the bottom of racemes. Both female and perfect flower production tended to increase proportionately with plant size in gynomonoecious individuals. Female flowers did not produce less biomass than perfect flowers from hermaphroditic or gynomonoecious plants. However, both female and perfect flowers from gynomonoecious individuals had lighter stamen mass, but larger pistil mass, than perfect flowers from hermaphrodites. Although the prediction of an increase in female flower number with plant size was not observed in E. anisopterus , the flexibility of sex allocation in gynomonoecious species was confirmed in that gynomonoecious individuals had a female-biased floral allocation compared to hermaphroditic individuals. Such comparisons of gynomonoecious to hermaphroditic individuals permit us to unveil a sexual adjustment strategy: flexibility of sexual investments within plants. © 2017 Botanical Society of America.

The Health Resources Allocation Model (HRAM) for the 21st century.

PubMed

Maire, Nicolas; Hegnauer, Michael; Nguyen, Dana; Godelmann, Lucas; Hoffmann, Axel; de Savigny, Don; Tanner, Marcel

2012-05-01

The Health Resources Allocation Model (HRAM) is an eLearning tool for health cadres and scientists introducing basic concepts of sub-national, rational district-based health planning and systems thinking under resources constraint. HRAM allows the evaluation of resource allocation strategies in relation to key outcome measures such as coverage, equity of services achieved and number of deaths and disability-adjusted life years (DALYs) prevented. In addition, the model takes into account geographical and demographic characteristics and populations' health seeking behaviour. It can be adapted to different socio-ecological and health system settings.

Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

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

Ramamurthy, Byravamurthy

2014-05-05

In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published severalmore » conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.« less

From Districts to Schools: The Distribution of Resources across Schools in Big City School Districts

ERIC Educational Resources Information Center

Rubenstein, Ross; Schwartz, Amy Ellen; Stiefel, Leanna; Amor, Hella Bel Hadj

2007-01-01

While the distribution of resources across school districts is well studied, relatively little attention has been paid to how resources are allocated to individual schools inside those districts. This paper explores the determinants of resource allocation across schools in large districts based on factors that reflect differential school costs or…

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

resource management decisions . Despite the lack of programming support, the use of multiple processor systems has grown sub- -stantially. Software has...making resource management decisions . Specifically, program- 1 mers need not allocate specific hardware resources to individual program components...Instead, such allocation decisions are automatically made based on high-level resource directives stated by ap- plication programmers, where each directive

Real-time distributed scheduling algorithm for supporting QoS over WDM networks

NASA Astrophysics Data System (ADS)

Kam, Anthony C.; Siu, Kai-Yeung

1998-10-01

Most existing or proposed WDM networks employ circuit switching, typically with one session having exclusive use of one entire wavelength. Consequently they are not suitable for data applications involving bursty traffic patterns. The MIT AON Consortium has developed an all-optical LAN/MAN testbed which provides time-slotted WDM service and employs fast-tunable transceivers in each optical terminal. In this paper, we explore extensions of this service to achieve fine-grained statistical multiplexing with different virtual circuits time-sharing the wavelengths in a fair manner. In particular, we develop a real-time distributed protocol for best-effort traffic over this time-slotted WDM service with near-optical fairness and throughput characteristics. As an additional design feature, our protocol supports the allocation of guaranteed bandwidths to selected connections. This feature acts as a first step towards supporting integrated services and quality-of-service guarantees over WDM networks. To achieve high throughput, our approach is based on scheduling transmissions, as opposed to collision- based schemes. Our distributed protocol involves one MAN scheduler and several LAN schedulers (one per LAN) in a master-slave arrangement. Because of propagation delays and limits on control channel capacities, all schedulers are designed to work with partial, delayed traffic information. Our distributed protocol is of the `greedy' type to ensure fast execution in real-time in response to dynamic traffic changes. It employs a hybrid form of rate and credit control for resource allocation. We have performed extensive simulations, which show that our protocol allocates resources (transmitters, receivers, wavelengths) fairly with high throughput, and supports bandwidth guarantees.

Medical resource preparation and allocation for humanitarian assistance based on module organization.

PubMed

Zhu, Min; Chen, Ruxue; Zhong, Shaobo; Qian, Yangming; Huang, Quanyi

2017-02-01

This research aims to associate the allocation of medical resources with the function of the modular organization and the possible needs for humanitarian assistance missions. The overseas humanitarian medical assistance mission, which was sent after a disaster on the hospital ship Peace Ark, part of China's People's Liberation Army (PLA) Navy, was considered as study model. The cases used for clustering and matching sample formation were randomly selected from the existing information related to Peace Ark's mission. Categories of the reusable resources clustered by this research met the requirement of the actual consumption almost completely (more than 95%) and the categories of non-reusable resources met the requirement by more than 80%. In the mission's original resource preparing plan, more than 30% of the non-reusable resource categories remained unused during the mission. In the original resource preparing plan, some key non-reusable resources inventories were completely exhausted at the end of the mission, while 5% to 30% of non-reusable resources remained in the resource allocation plan generated by this research at the end of the mission. The medical resource allocation plan generated here can enhance the supporting level for the humanitarian assistance mission. This research could lay the foundation for an assistant decision-making system for humanitarian assistance mission.

Improving the Success of Strategic Management Using Big Data.

PubMed

Desai, Sapan S; Wilkerson, James; Roberts, Todd

2016-01-01

Strategic management involves determining organizational goals, implementing a strategic plan, and properly allocating resources. Poor access to pertinent and timely data misidentifies clinical goals, prevents effective resource allocation, and generates waste from inaccurate forecasting. Loss of operational efficiency diminishes the value stream, adversely impacts the quality of patient care, and hampers effective strategic management. We have pioneered an approach using big data to create competitive advantage by identifying trends in clinical practice, accurately anticipating future needs, and strategically allocating resources for maximum impact.

Regional Disparities in the Allocation of China's Higher Education Resources from the Perspective of Equity

ERIC Educational Resources Information Center

Wei, Bao

2012-01-01

This article attempts to analyze the changing circumstances of the regional disparities in the allocation of China's higher educational resources before and after the increase in college enrollments, as well as the mechanisms that have affected these circumstances. The conclusions are that regional disparities in the allocation of China's funding…

Resources for health promotion: rhetoric, research and reality.

PubMed

Minke, Sharlene Wolbeck; Raine, Kim D; Plotnikoff, Ronald C; Anderson, Donna; Khalema, Ernest; Smith, Cynthia

2007-01-01

Canadian political discourse supports the importance of health promotion and advocates the allocation of health resources to health promotion. Furthermore, the current literature frequently identifies financial and human resources as important elements of organizational capacity for health promotion. In the Alberta Heart Health Project (AHHP), we sought to learn if the allocation of health resources in a regionalized health system was congruent with the espoused support for health promotion in Alberta, Canada. The AHHP used a mixed method approach in a time series design. Participants were drawn from multiple organizational levels (i.e., service providers, managers, board members) across all Regional Health Authorities (RHAs). Data were triangulated through multiple collection methods, primarily an organizational capacity survey, analysis of organizational documents, focus groups, and personal interviews. Analysis techniques were drawn from quantitative (i.e., frequency distributions, ANOVAs) and qualitative (i.e., content and thematic analysis) approaches. In most cases, small amounts (<5%) of financial resources were allocated to health promotion in RHAs' core budgets. Respondents reported seeking multiple sources of public health financing to support their health promotion initiatives. Human resources for health promotion were characterized by fragmented responsibilities and short-term work. Furthermore, valuable human resources were consumed in ongoing searches for funding that typically covered short time periods. Resource allocations to health promotion in Alberta RHAs are inconsistent with the current emphasis on health promotion as an organizational priority. Inadequate and unstable funding erodes the RHAs' capacity for health promotion. Sustainable health promotion calls for the assured allocation of adequate, sustainable financial resources.

Optimal Power Allocation for CC-HARQ-based Cognitive Radio with Statistical CSI in Nakagami Slow Fading Channels

NASA Astrophysics Data System (ADS)

Xu, Ding; Li, Qun

2017-01-01

This paper addresses the power allocation problem for cognitive radio (CR) based on hybrid-automatic-repeat-request (HARQ) with chase combining (CC) in Nakagamimslow fading channels. We assume that, instead of the perfect instantaneous channel state information (CSI), only the statistical CSI is available at the secondary user (SU) transmitter. The aim is to minimize the SU outage probability under the primary user (PU) interference outage constraint. Using the Lagrange multiplier method, an iterative and recursive algorithm is derived to obtain the optimal power allocation for each transmission round. Extensive numerical results are presented to illustrate the performance of the proposed algorithm.

Successive equimarginal approach for optimal design of a pump and treat system

NASA Astrophysics Data System (ADS)

Guo, Xiaoniu; Zhang, Chuan-Mian; Borthwick, John C.

2007-08-01

An economic concept-based optimization method is developed for groundwater remediation design. Design of a pump and treat (P&T) system is viewed as a resource allocation problem constrained by specified cleanup criteria. An optimal allocation of resources requires that the equimarginal principle, a fundamental economic principle, must hold. The proposed method is named successive equimarginal approach (SEA), which continuously shifts a pumping rate from a less effective well to a more effective one until equal marginal productivity for all units is reached. Through the successive process, the solution evenly approaches the multiple inequality constraints that represent the specified cleanup criteria in space and in time. The goal is to design an equal protection system so that the distributed contaminant plumes can be equally contained without bypass and overprotection is minimized. SEA is a hybrid of the gradient-based method and the deterministic heuristics-based method, which allows flexibility in dealing with multiple inequality constraints without using a penalty function and in balancing computational efficiency with robustness. This method was applied to design a large-scale P&T system for containment of multiple plumes at the former Blaine Naval Ammunition Depot (NAD) site, near Hastings, Nebraska. To evaluate this method, the SEA results were also compared with those using genetic algorithms.

A Greedy Double Auction Mechanism for Grid Resource Allocation

NASA Astrophysics Data System (ADS)

Ding, Ding; Luo, Siwei; Gao, Zhan

To improve the resource utilization and satisfy more users, a Greedy Double Auction Mechanism(GDAM) is proposed to allocate resources in grid environments. GDAM trades resources at discriminatory price instead of uniform price, reflecting the variance in requirements for profits and quantities. Moreover, GDAM applies different auction rules to different cases, over-demand, over-supply and equilibrium of demand and supply. As a new mechanism for grid resource allocation, GDAM is proved to be strategy-proof, economically efficient, weakly budget-balanced and individual rational. Simulation results also confirm that GDAM outperforms the traditional one on both the total trade amount and the user satisfaction percentage, specially as more users are involved in the auction market.

Optimal resource allocation for novelty detection in a human auditory memory.

PubMed

Sinkkonen, J; Kaski, S; Huotilainen, M; Ilmoniemi, R J; Näätänen, R; Kaila, K

1996-11-04

A theory of resource allocation for neuronal low-level filtering is presented, based on an analysis of optimal resource allocation in simple environments. A quantitative prediction of the theory was verified in measurements of the magnetic mismatch response (MMR), an auditory event-related magnetic response of the human brain. The amplitude of the MMR was found to be directly proportional to the information conveyed by the stimulus. To the extent that the amplitude of the MMR can be used to measure resource usage by the auditory cortex, this finding supports our theory that, at least for early auditory processing, energy resources are used in proportion to the information content of incoming stimulus flow.

Allocative and implementation efficiency in HIV prevention and treatment for people who inject drugs.

PubMed

Benedikt, Clemens; Kelly, Sherrie L; Wilson, David; Wilson, David P

2016-12-01

Estimated global new HIV infections among people who inject drugs (PWID) remained stable over the 2010-2015 period and the target of a 50% reduction over this period was missed. To achieve the 2020 UNAIDS target of reducing adult HIV infections by 75% compared to 2010, accelerated action in scaling up HIV programs for PWID is required. In a context of diminishing external support to HIV programs in countries where most HIV-affected PWID live, it is essential that available resources are allocated and used as efficiently as possible. Allocative and implementation efficiency analysis methods were applied. Optima, a dynamic, population-based HIV model with an integrated program and economic analysis framework was applied in eight countries in Eastern Europe and Central Asia (EECA). Mathematical analyses established optimized allocations of resources. An implementation efficiency analysis focused on examining technical efficiency, unit costs, and heterogeneity of service delivery models and practices. Findings from the latest reported data revealed that countries allocated between 4% (Bulgaria) and 40% (Georgia) of total HIV resources to programs targeting PWID - with a median of 13% for the eight countries. When distributing the same amount of HIV funding optimally, between 9% and 25% of available HIV resources would be allocated to PWID programs with a median allocation of 16% and, in addition, antiretroviral therapy would be scaled up including for PWID. As a result of optimized allocations, new HIV infections are projected to decline by 3-28% and AIDS-related deaths by 7-53% in the eight countries. Implementation efficiencies identified involve potential reductions in drug procurement costs, service delivery models, and practices and scale of service delivery influencing cost and outcome. A high level of implementation efficiency was associated with high volumes of PWID clients accessing a drug harm reduction facility. A combination of optimized allocation of resources, improved implementation efficiency and increased investment of non-HIV resources is required to enhance coverage and improve outcomes of programs for PWID. Increasing efficiency of HIV programs for PWID is a key step towards avoiding implicit rationing and ensuring transparent allocation of resources where and how they would have the largest impact on the health of PWID, and thereby ensuring that funding spent on PWID becomes a global best buy in public health. Copyright © 2016. Published by Elsevier B.V.

Runway Operations Planning: A Two-Stage Heuristic Algorithm

NASA Technical Reports Server (NTRS)

Anagnostakis, Ioannis; Clarke, John-Paul

2003-01-01

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, can also be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. This paper introduces a two stage heuristic algorithm for solving the Runway Operations Planning (ROP) problem. In the first stage, sequences of departure class slots and runway crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program with a Branch & Bound algorithm implementation. Preliminary results from this implementation of the two-stage algorithm on real-world traffic data are presented.

CAD-Based Aerodynamic Design of Complex Configurations using a Cartesian Method

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.

2003-01-01

A modular framework for aerodynamic optimization of complex geometries is developed. By working directly with a parametric CAD system, complex-geometry models are modified nnd tessellated in an automatic fashion. The use of a component-based Cartesian method significantly reduces the demands on the CAD system, and also provides for robust and efficient flowfield analysis. The optimization is controlled using either a genetic or quasi-Newton algorithm. Parallel efficiency of the framework is maintained even when subject to limited CAD resources by dynamically re-allocating the processors of the flow solver. Overall, the resulting framework can explore designs incorporating large shape modifications and changes in topology.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

PubMed

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler

NASA Astrophysics Data System (ADS)

Huang, Ye; Brocco, Amos; Courant, Michele; Hirsbrunner, Beat; Kuonen, Pierre

This paper presents a simulator for of a decentralized modular grid scheduler named MaGate. MaGate’s design emphasizes scheduler interoperability by providing intelligent scheduling serving the grid community as a whole. Each MaGate scheduler instance is able to deal with dynamic scheduling conditions, with continuously arriving grid jobs. Received jobs are either allocated on local resources, or delegated to other MaGates for remote execution. The proposed MaGate simulator is based on GridSim toolkit and Alea simulator, and abstracts the features and behaviors of complex fundamental grid elements, such as grid jobs, grid resources, and grid users. Simulation of scheduling tasks is supported by a grid network overlay simulator executing distributed ant-based swarm intelligence algorithms to provide services such as group communication and resource discovery. For evaluation, a comparison of behaviors of different collaborative policies among a community of MaGates is provided. Results support the use of the proposed approach as a functional ready grid scheduler simulator.

Ranking in evolving complex networks

NASA Astrophysics Data System (ADS)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Money, Time and Learning. Final Report.

ERIC Educational Resources Information Center

Thomas, J. Alan; Kemmerer, Frances

Chapter 1 of this study discusses sources of educational inequality in terms of criteria for resource allocation, definitions of educational equity, and equity and efficiency in the classroom. Following the second chapter's review of literature on how resources affect learning, chapter 3 offers a theory of resource allocation education. The fourth…

Children's Allocation of Resources in Social Dominance Situations

ERIC Educational Resources Information Center

Charafeddine, Rawan; Mercier, Hugo; Clément, Fabrice; Kaufmann, Laurence; Reboul, Anne; Van der Henst, Jean-Baptiste

2016-01-01

Two experiments with preschoolers (36 to 78 months) and 8-year-old children (Experiment 1, N = 173; Experiment 2, N = 132) investigated the development of children's resource distribution in dominance contexts. On the basis of the distributive justice literature, 2 opposite predictions were tested. Children could match resource allocation with the…

Self-benefiting in the allocation of scarce resources: leader-follower effects and the moderating effect of social value orientations.

PubMed

van Dijk, Eric; De Cremer, David

2006-10-01

Previous research on the allocation of scarce resources suggests that people who are assigned to higher positions (e.g., leaders) are more likely to make self-benefiting allocations than people who are assigned to lower positions (e.g., followers). In this article, the authors investigated the proposition that these findings would be moderated by people's social value orientations. In two experimental studies, the authors assigned participants either to the role of leader or follower and assessed the participants' social value orientations. In agreement with predictions, the findings show that position effects are moderated by social value orientation. Social value orientations only affected the allocation behavior of the leaders: Proself leaders allocated more resources to themselves than did prosocial leaders. Additional analyses indicate that these effects are mediated by feelings of entitlement.

Capacity improvement using simulation optimization approaches: A case study in the thermotechnology industry

NASA Astrophysics Data System (ADS)

Yelkenci Köse, Simge; Demir, Leyla; Tunalı, Semra; Türsel Eliiyi, Deniz

2015-02-01

In manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality.

Algorithmic Coordination in Robotic Networks

DTIC Science & Technology

2010-11-29

appropriate performance, robustness and scalability properties for various task allocation , surveillance, and information gathering applications is...networking, we envision designing and analyzing algorithms with appropriate performance, robustness and scalability properties for various task ...distributed algorithms for target assignments; based on the classic auction algorithms in static networks, we intend to design efficient algorithms in worst

The Named-State Register File

DTIC Science & Technology

1993-08-01

on the Lempel - Ziv [44] algo- rithm. Zip is compressing a single 8,017 byte file. " RTLSim An register transfer language simulator for the Message...package. gordoni@cs.adelaide.edu.au, Wynn Vale, 5127, Australia, 1.0 edition, October 1991. [44] Ziv J. and Lempel A. "A universal algorithm for...fixed hardware algorithm . Some data caches allow the program to explicitly allocate cache lines [68]. This allocation is only useful in writing new data

[Mechanisms for allocating financial resources after decentralization in the state of Jalisco].

PubMed

Pérez-Núñez, Ricardo; Arredondo-López, Armando; Pelcastre, Blanca

2006-01-01

To analyze, from the decision maker's perspective, the financial resource allocation process of the health services of the state of Jalisco (SSJ, per its abbreviation in spanish), within the context of decentralization. Through a qualitative approximation using semi-structured individual interviews of key personnel in managerial positions as the method for compiling information, the experience of the SSJ in financial resource allocation was documented. From September to November 2003, the perception of managers and administrators regarding their level of autonomy in decision-making was explored as well as the process they follow for the allocation of financial resources, in order to identify the criteria they use and their justifications. From the point of view of decision-makers, autonomy of the SSJ has increased considerably since decentralization was implemented, although the degree of decision-making freedom remains limited due mainly to high adminstrative costs associated with salaries. In this sense, the implications attributable to labor situations that are still centralized are evident. Some innovative systems for financial resource allocation have been established in the SSJ for the sanitary regions and hospitals based upon administrative-managerial and productivity incentives. Adjustments were also made for degree of marginalization and population lag, under the equity criterion. General work conditions and decision-making autonomy of the sanitary regions constitute outstanding aspects pending decentralization. Although decentralization has granted more autonomy to the SSJ, the level of decision-making freedom for allocating financial resources has been held within the highest hierarchical levels.

[Strategic decisions in public psychiatric institutions: a proposed method for resource analysis and allocation].

PubMed

Micheletti, Pierre; Chierici, Piero; Durang, Xavier; Salvador, Nathalie; Lopez, Nathalie

2011-01-01

Because of its sector-based organization and extra-hospital care, public psychiatry has a unique position in healthcare. This paper describes the tools and procedures used to analyze and allocate the resources of the "Centre Hospitalier Alpes-Isère", a hospital serving a catchment population of 530,000 adults. A consensus-based approach was used to validate the selected indicators and included the participation of a geographer. Five levels of resource allocation were identified and classified using a decision tree. At each level, the relevant authorities and criteria were identified as key components of the decision-making process. This paper describes the first three levels of care provision. Focusing on adult care, a comparative assessment of the resources allocated to general psychiatric care and specialist care was conducted, in addition to a comparative assessment of the resources allocated to each of the hospital's four local centers. Geographical accessibility to extramural facilities was also assessed. A study of the characteristics of each general psychiatry clinic revealed significant disparities. The paper highlights several issues: the poor knowledge of psychiatric epidemiological data relating to the population within the catchment area, the difficulty of assessing non-consolidated data or indicators from multiple sources, and the limited and partial nature of geographical data for characterizing and evaluating health care in the hospital's peripheral clinics. Several studies are currently underway to assess the operational effectiveness of the tools and procedures used to analyze and allocate resources.

Cost of equity in homeland security resource allocation in the face of a strategic attacker.

PubMed

Shan, Xiaojun; Zhuang, Jun

2013-06-01

Hundreds of billions of dollars have been spent in homeland security since September 11, 2001. Many mathematical models have been developed to study strategic interactions between governments (defenders) and terrorists (attackers). However, few studies have considered the tradeoff between equity and efficiency in homeland security resource allocation. In this article, we fill this gap by developing a novel model in which a government allocates defensive resources among multiple potential targets, while reserving a portion of defensive resources (represented by the equity coefficient) for equal distribution (according to geographical areas, population, density, etc.). Such a way to model equity is one of many alternatives, but was directly inspired by homeland security resource allocation practice. The government is faced with a strategic terrorist (adaptive adversary) whose attack probabilities are endogenously determined in the model. We study the effect of the equity coefficient on the optimal defensive resource allocations and the corresponding expected loss. We find that the cost of equity (in terms of increased expected loss) increases convexly in the equity coefficient. Furthermore, such cost is lower when: (a) government uses per-valuation equity; (b) the cost-effectiveness coefficient of defense increases; and (c) the total defense budget increases. Our model, results, and insights could be used to assist policy making. © 2012 Society for Risk Analysis.

Land Resources Allocation Strategies in an Urban Area Involving Uncertainty: A Case Study of Suzhou, in the Yangtze River Delta of China

NASA Astrophysics Data System (ADS)

Lu, Shasha; Guan, Xingliang; Zhou, Min; Wang, Yang

2014-05-01

A large number of mathematical models have been developed to support land resource allocation decisions and land management needs; however, few of them can address various uncertainties that exist in relation to many factors presented in such decisions (e.g., land resource availabilities, land demands, land-use patterns, and social demands, as well as ecological requirements). In this study, a multi-objective interval-stochastic land resource allocation model (MOISLAM) was developed for tackling uncertainty that presents as discrete intervals and/or probability distributions. The developed model improves upon the existing multi-objective programming and inexact optimization approaches. The MOISLAM not only considers economic factors, but also involves food security and eco-environmental constraints; it can, therefore, effectively reflect various interrelations among different aspects in a land resource management system. Moreover, the model can also help examine the reliability of satisfying (or the risk of violating) system constraints under uncertainty. In this study, the MOISLAM was applied to a real case of long-term urban land resource allocation planning in Suzhou, in the Yangtze River Delta of China. Interval solutions associated with different risk levels of constraint violation were obtained. The results are considered useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify a desirable land resource allocation strategy under uncertainty.

Influence of mate preference and laying order on maternal allocation in a monogamous parrot species with extreme hatching asynchrony.

PubMed

Lahaye, Stefanie E P; Eens, Marcel; Iserbyt, Arne; Groothuis, Ton G G; de Vries, Bonnie; Müller, Wendt; Pinxten, Rianne

2015-05-01

It is well established that in many avian species, prenatal maternal resource allocation varies both between and within clutches and may affect offspring fitness. Differential allocation of maternal resources, in terms of egg weight and yolk composition, may therefore allow the female to adjust brood reduction and to fine-tune reproductive investment in accordance with the expected fitness returns. The adaptive value of such maternal resource allocation is thought to be context-dependent as well as species-specific. We investigated the effects of female preference for her mate on the allocation of prenatal maternal resources in the budgerigar, Melopsittacus undulatus, a monogamous species of parrot that shows an extreme hatching asynchrony. We assessed mate preferences in a two-way preference test and allowed females two breeding rounds: one with the preferred and one with the non-preferred partner. We found no effect of preference on either latency to lay or clutch size, but females mated with the preferred partner laid eggs that contained significantly more yolk. Their eggs also contained significantly more androstenedione but not testosterone. Our results suggest that in this species, female preference may influence maternal resource allocation, and that the functional roles of each androgen in the yolk should be considered separately. In addition, we found a significant effect of laying order on egg and yolk weight as well as on yolk testosterone and androstenedione levels. These measures, however, did not change linearly with the laying order and render it unlikely that female budgerigars compensate for the extreme hatching asynchrony by adjusting within-clutch allocation of prenatal maternal resources. Copyright © 2015 Elsevier Inc. All rights reserved.

Local search to improve coordinate-based task mapping

DOE PAGES

Balzuweit, Evan; Bunde, David P.; Leung, Vitus J.; ...

2015-10-31

We present a local search strategy to improve the coordinate-based mapping of a parallel job’s tasks to the MPI ranks of its parallel allocation in order to reduce network congestion and the job’s communication time. The goal is to reduce the number of network hops between communicating pairs of ranks. Our target is applications with a nearest-neighbor stencil communication pattern running on mesh systems with non-contiguous processor allocation, such as Cray XE and XK Systems. Utilizing the miniGhost mini-app, which models the shock physics application CTH, we demonstrate that our strategy reduces application running time while also reducing the runtimemore » variability. Furthermore, we further show that mapping quality can vary based on the selected allocation algorithm, even between allocation algorithms of similar apparent quality.« less

Waste management: how reducing partiality can promote efficient resource allocation.

PubMed

Choshen-Hillel, Shoham; Shaw, Alex; Caruso, Eugene M

2015-08-01

Two central principles that guide resource-allocation decisions are equity (providing equal pay for equal work) and efficiency (not wasting resources). When these two principles conflict with one another, people will often waste resources to avoid inequity. We suggest that people wish to avoid inequity not because they find it inherently unfair, but because they want to avoid the appearance of partiality associated with it. We explore one way to reduce waste by reducing the perceived partiality of inequitable allocations. Specifically, we hypothesize that people will be more likely to favor an efficient (albeit inequitable) allocation if it puts them in a disadvantaged position than if it puts others in a disadvantaged position. To test this hypothesis, we asked participants to choose between giving some extra resource to one person (thereby creating inequity between this person and equally deserving others) and not giving the resource to anyone (thereby wasting the resource). Six studies, using realistic scenarios and behavioral paradigms, provide robust evidence for a self-disadvantaging effect: Allocators were consistently more likely to create inequity to avoid wasting resources when the resulting inequity would put them at a relative disadvantage than when it would put others at a relative disadvantage. We further find that this self-disadvantaging effect is a direct result of people's concern about appearing partial. Our findings suggest the importance of impartiality even in distributive justice, thereby bridging a gap between the distributive and procedural justice literatures. (c) 2015 APA, all rights reserved.

Allocation of Health Resources According To the Type and Size of Iranian Governmental Hospitals

PubMed Central

Hassani, SA; Abolhallaje, M; Inanlo, S; Hosseini, H; Pourmohammadi, K; Bastani, P; Ramezanian, M; Marnani, A Barati

2013-01-01

Background: Due to consuming about 50%–80% of health resources, hospitals are the greatest and costly operational units in Iranian Health system. so allocation of resources specially human and space resources as the most expensive ones is really important for further controlling of costs, analysis of costs and making suitable policies for increasing the profitability and allocation of resources and improvement of quality. Method: This paper intends to describe and analyze any allocation of resources in 530 university hospitals in Iran. The final goal of this research is to provide a data bank according which there is a basis for more scientific budget allocation of state’s hospitals from the size and type of application points of view. Results: The relevant index of person to bed was 2.04 for human resources. All hospitals more than 300 beds are located in benefiting areas from which 17 cases are educational and 2 cases are therapeutic. This is necessary to mention that the rate of management group forces to total personnel at deprived areas is about 2.5% more than benefiting areas. Conclusion: Because 60–80% of hospital costs are applied for human forces, all managers of hospitals are obliged to revise their policies in attraction and employment of human force in order to benefit from such a valuable resource and prevent from expensive costs. So any employment of personnel should be based upon real needs of hospital. PMID:23865036

Effect of physician perspective on allocation of Medicare resources for patients with advanced cancer.

PubMed

Rocke, Daniel J; Beumer, Halton W; Thomas, Steven; Lee, Walter T

2014-05-01

To assess how physician perspective (perspective of patient vs perspective of physician) affects Medicare resource allocation for patients with advanced cancer and compare physician allocations with actual cancer patient and caregiver allocations. Cross-sectional assessment. National assessment. Otolaryngologists. Physicians used a validated tool to create a Medicare plan for patients with advanced cancer. Participants took the perspective of an advanced cancer patient and made resource allocations between 15 benefit categories (assessment 2, November/December 2012). Results were compared with data from a prior assessment made from a physician's perspective (assessment 1, February/March 2012) and with data from a separate study with patients with cancer and caregivers. In total, 767 physicians completed assessment 1 and 237 completed assessment 2. Results were compared with 146 cancer patient and 114 caregiver assessments. Assessment 1 physician responses differed significantly from patients/caregivers in 14 categories (P < .05), while assessment 2 differed in 11. When comparing physician data, assessment 2 allocations differed significantly from assessment 1 in 7 categories. When these 7 categories were compared with patient/caregiver data, assessment 2 allocations in emotional care, drug coverage, and nursing facility categories were not significantly different. Assessment 1 allocations in cosmetic care, dental, home care, and primary care categories were more similar to patient/caregiver preferences, although all but home care were still significantly different. Otolaryngology-head and neck surgery physician perspectives on end-of-life care differ significantly from cancer patient/caregiver perspectives, even when physicians take a patient's perspective when allocating resources. This demonstrates the challenges inherent in end-of-life discussions.

An algorithm for calculating exam quality as a basis for performance-based allocation of funds at medical schools.

PubMed

Kirschstein, Timo; Wolters, Alexander; Lenz, Jan-Hendrik; Fröhlich, Susanne; Hakenberg, Oliver; Kundt, Günther; Darmüntzel, Martin; Hecker, Michael; Altiner, Attila; Müller-Hilke, Brigitte

2016-01-01

The amendment of the Medical Licensing Act (ÄAppO) in Germany in 2002 led to the introduction of graded assessments in the clinical part of medical studies. This, in turn, lent new weight to the importance of written tests, even though the minimum requirements for exam quality are sometimes difficult to reach. Introducing exam quality as a criterion for the award of performance-based allocation of funds is expected to steer the attention of faculty members towards more quality and perpetuate higher standards. However, at present there is a lack of suitable algorithms for calculating exam quality. In the spring of 2014, the students' dean commissioned the "core group" for curricular improvement at the University Medical Center in Rostock to revise the criteria for the allocation of performance-based funds for teaching. In a first approach, we developed an algorithm that was based on the results of the most common type of exam in medical education, multiple choice tests. It included item difficulty and discrimination, reliability as well as the distribution of grades achieved. This algorithm quantitatively describes exam quality of multiple choice exams. However, it can also be applied to exams involving short assay questions and the OSCE. It thus allows for the quantitation of exam quality in the various subjects and - in analogy to impact factors and third party grants - a ranking among faculty. Our algorithm can be applied to all test formats in which item difficulty, the discriminatory power of the individual items, reliability of the exam and the distribution of grades are measured. Even though the content validity of an exam is not considered here, we believe that our algorithm is suitable as a general basis for performance-based allocation of funds.

A system dynamics model of a large R&D program

NASA Astrophysics Data System (ADS)

Ahn, Namsung

Organizations with large R&D activities must deal with a hierarchy of decision regarding resource allocation. At the highest level of allocation, the decision is related to the total allocation to R&D as some portion of revenue. The middle level of allocation deals with the allocation among phases of the R&D process. The lowest level of decisions relates to the resource allocation to specific projects within a specific phase. This study focuses on developing an R&D model to deal with the middle level of allocation, i.e., the allocation among phases of research such as basic research, development, and demonstration. The methodology used to develop the R&D model is System Dynamics. Our modeling concept is innovative in representing each phase of R&D as consisting of two parts: projects under way, and an inventory of successful but not-yet- exploited projects. In a simple world, this concept can yield an exact analytical solution for allocation of resources among phases. But in a real world, the concept should be improved by adding more complex structures with nonlinear behaviors. Two particular nonlinear feedbacks are incorporated into the R&D model. The probability of success for any specific project is assumed partly dependent upon resources allocated to the project. Further, the time required to reach a conclusion regarding the success or failure of a project is also assumed dependent upon the level of resources allocated. In addition, the number of successful projects partly depends on the inventory of potential ideas in the previous stage that can be exploited. This model can provide R&D management with insights into the effect of changing allocations to phases whether those changes are internally or externally driven. With this model, it is possible to study the effectiveness of management decisions in a continuous fashion. Managers can predict payoffs for a host of different policies. In addition, as new research results accumulate, a re- assessment of program goals can be implemented easily and allocations adjusted to enhance continuously the likelihood of success, and to optimize payoffs. Finally, this model can give managers a quantitative rationale for program evaluation and permit the quantitative assessment of various externally imposed changes. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Decision maker perceptions of resource allocation processes in Canadian health care organizations: a national survey.

PubMed

Smith, Neale; Mitton, Craig; Bryan, Stirling; Davidson, Alan; Urquhart, Bonnie; Gibson, Jennifer L; Peacock, Stuart; Donaldson, Cam

2013-07-02

Resource allocation is a key challenge for healthcare decision makers. While several case studies of organizational practice exist, there have been few large-scale cross-organization comparisons. Between January and April 2011, we conducted an on-line survey of senior decision makers within regional health authorities (and closely equivalent organizations) across all Canadian provinces and territories. We received returns from 92 individual managers, from 60 out of 89 organizations in total. The survey inquired about structures, process features, and behaviours related to organization-wide resource allocation decisions. We focus here on three main aspects: type of process, perceived fairness, and overall rating. About one-half of respondents indicated that their organization used a formal process for resource allocation, while the others reported that political or historical factors were predominant. Seventy percent (70%) of respondents self-reported that their resource allocation process was fair and just over one-half assessed their process as 'good' or 'very good'. This paper explores these findings in greater detail and assesses them in context of the larger literature. Data from this large-scale cross-jurisdictional survey helps to illustrate common challenges and areas of positive performance among Canada's health system leadership teams.

Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

PubMed

Averill, Colin

2014-10-01

Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate. © 2014 John Wiley & Sons Ltd/CNRS.

Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud

PubMed Central

Florence, A. Paulin; Shanthi, V.; Simon, C. B. Sunil

2016-01-01

Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption. PMID:27239551

Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud.

PubMed

Florence, A Paulin; Shanthi, V; Simon, C B Sunil

2016-01-01

Cloud computing is a new technology which supports resource sharing on a "Pay as you go" basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

PubMed

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon; Cho, Sungrae

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform

PubMed Central

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively. PMID:28796804

Optimal Resource Allocation in Library Systems

ERIC Educational Resources Information Center

Rouse, William B.

1975-01-01

Queueing theory is used to model processes as either waiting or balking processes. The optimal allocation of resources to these processes is defined as that which maximizes the expected value of the decision-maker's utility function. (Author)

Resource allocation in shared spectrum access communications for operators with diverse service requirements

NASA Astrophysics Data System (ADS)

Kibria, Mirza Golam; Villardi, Gabriel Porto; Ishizu, Kentaro; Kojima, Fumihide; Yano, Hiroyuki

2016-12-01

In this paper, we study inter-operator spectrum sharing and intra-operator resource allocation in shared spectrum access communication systems and propose efficient dynamic solutions to address both inter-operator and intra-operator resource allocation optimization problems. For inter-operator spectrum sharing, we present two competent approaches, namely the subcarrier gain-based sharing and fragmentation-based sharing, which carry out fair and flexible allocation of the available shareable spectrum among the operators subject to certain well-defined sharing rules, traffic demands, and channel propagation characteristics. The subcarrier gain-based spectrum sharing scheme has been found to be more efficient in terms of achieved throughput. However, the fragmentation-based sharing is more attractive in terms of computational complexity. For intra-operator resource allocation, we consider resource allocation problem with users' dissimilar service requirements, where the operator supports users with delay constraint and non-delay constraint service requirements, simultaneously. This optimization problem is a mixed-integer non-linear programming problem and non-convex, which is computationally very expensive, and the complexity grows exponentially with the number of integer variables. We propose less-complex and efficient suboptimal solution based on formulating exact linearization, linear approximation, and convexification techniques for the non-linear and/or non-convex objective functions and constraints. Extensive simulation performance analysis has been carried out that validates the efficiency of the proposed solution.

Challenges associated with tracking resources allocation for reproductive health in sub-Saharan African countries: the UNFPA/NIDI resource flows project experience.

PubMed

Sidze, Estelle M; Beekink, Erik; Maina, Beatrice W

2015-05-05

Universal access to reproductive health services entails strengthening health systems, but requires significant resource commitments as well as efficient and effective use of those resources. A number of international organizations and governments in developing countries are putting efforts into tracking the flow of health resources in order to inform resource mobilization and allocation, strategic planning, priority setting, advocacy and general policy making. The UNFPA/NIDI-led Resource Flows Project ("The UNFPA/NIDI RF Project") has conducted annual surveys since 1997 to monitor progress achieved by developing countries in implementing reproductive health financial targets. This commentary summarizes the Project experiences and challenges in gathering data on allocation of resources for reproductive health at the domestic level in sub-Saharan African countries. One key lesson learnt from the Project experience is the need for strengthening tracking mechanisms in sub-Saharan African countries and making information on reproductive health resources and expenditures available, in particular the private sector resources.

Service guidelines based on Resource Utilization Groups Version III for Home Care provide decision-making support for case managers.

PubMed

Collister, Barbara; Stein, Glenda; Katz, Deborah; DeBruyn, Joan; Andrusiw, Linda; Cloutier, Sheila

2012-01-01

Increasing costs and budget reductions combined with increasing demand from our growing, aging population support the need to ensure that the scarce resources allocated to home care clients match client needs. This article details how Integrated Home Care for the Calgary Zone of Alberta Health Services considered ethical and economic principles and used data from the Resident Assessment Instrument for Home Care (RAI-HC) and case mix indices from the Resource Utilization Groups Version III for Home Care (RUG-III/HC) to formulate service guidelines. These explicit service guidelines formalize and support individual resource allocation decisions made by case managers and provide a consistent and transparent method of allocating limited resources.

A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations.

PubMed

Evangelista, Daniela; Zuccaro, Antonio; Lančinskas, Algirdas; Žilinskas, Julius; Guarracino, Mario R

2016-02-17

The cost per patient of next generation sequencing for detection of rare mutations may be significantly reduced using pooled experiments. Recently, some techniques have been proposed for the planning of pooled experiments and for the optimal allocation of patients into pools. However, the lack of a user friendly resource for planning the design of pooled experiments forces the scientists to do frequent, complex and long computations. OPENDoRM is a powerful collection of novel mathematical algorithms usable via an intuitive graphical user interface. It enables researchers to speed up the planning of their routine experiments, as well as, to support scientists without specific bioinformatics expertises. Users can automatically carry out analysis in terms of costs associated with the optimal allocation of patients in pools. They are also able to choose between three distinct pooling mathematical methods, each of which also suggests the optimal configuration for the submitted experiment. Importantly, in order to keep track of the performed experiments, users can save and export the results of their experiments in standard tabular and charts contents. OPENDoRM is a freely available web-oriented application for the planning of pooled NGS experiments, available at: http://www-labgtp.na.icar.cnr.it/OPENDoRM. Its easy and intuitive graphical user interface enables researchers to plan theirs experiments using novel algorithms, and to interactively visualize the results.

Informing the Gestalt: An Ethical Framework for Allocating Scarce Federal Public Health and Medical Resources to States During Disasters

PubMed Central

Knebel, Ann R.; Sharpe, Virginia A.; Danis, Marion; Toomey, Lauren M.; Knickerbocker, Deborah K.

2017-01-01

During catastrophic disasters, government leaders must decide how to efficiently and effectively allocate scarce public health and medical resources. The literature about triage decision making at the individual patient level is substantial, and the National Response Framework provides guidance about the distribution of responsibilities between federal and state governments. However, little has been written about the decision-making process of federal leaders in disaster situations when resources are not sufficient to meet the needs of several states simultaneously. We offer an ethical framework and logic model for decision making in such circumstances. We adapted medical triage and the federalism principle to the decision-making process for allocating scarce federal public health and medical resources. We believe that the logic model provides a values-based framework that can inform the gestalt during the iterative decision process used by federal leaders as they allocate scarce resources to states during catastrophic disasters. PMID:24612854

Ising game: Nonequilibrium steady states of resource-allocation systems

NASA Astrophysics Data System (ADS)

Xin, C.; Yang, G.; Huang, J. P.

2017-04-01

Resource-allocation systems are ubiquitous in the human society. But how external fields affect the state of such systems remains poorly explored due to the lack of a suitable model. Because the behavior of spins pursuing energy minimization required by physical laws is similar to that of humans chasing payoff maximization studied in game theory, here we combine the Ising model with the market-directed resource-allocation game, yielding an Ising game. Based on the Ising game, we show theoretical, simulative and experimental evidences for a formula, which offers a clear expression of nonequilibrium steady states (NESSs). Interestingly, the formula also reveals a convertible relationship between the external field (exogenous factor) and resource ratio (endogenous factor), and a class of saturation as the external field exceeds certain limits. This work suggests that the Ising game could be a suitable model for studying external-field effects on resource-allocation systems, and it could provide guidance both for seeking more relations between NESSs and equilibrium states and for regulating human systems by choosing NESSs appropriately.

Resource allocation using ANN in LTE

NASA Astrophysics Data System (ADS)

Yigit, Tuncay; Ersoy, Mevlut

2017-07-01

LTE is the 4th generation wireless network technology, which provides flexible bandwidth, higher data speeds and lower delay. Difficulties may be experienced upon an increase in the number of users in LTE. The objective of this study is to ensure a faster solution to any such resource allocation problems which might arise upon an increase in the number of users. A fast and effective solution has been obtained by making use of Artificial Neural Network. As a result, fast working artificial intelligence methods may be used in resource allocation problems during operation.

The Cost Structure of Higher Education: Implications for Governmental Policy in Steady State.

ERIC Educational Resources Information Center

Lyell, Edward H.

The historical pattern of resource allocation in American higher education as exemplified by public colleges in Colorado was examined. The reliance upon average cost information in making resource allocation decisions was critiqued for the special problems that arise from student enrollment decline or steady state. A model of resource allocation…

The Role of Research and Analysis in Resource Allocation Decisions

ERIC Educational Resources Information Center

Lea, Dennis; Polster, Patty Poppe

2011-01-01

In a time of diminishing resources and increased accountability, it is important for school leaders to make the most of every dollar they spend. One approach to ensuring responsible resource allocation is to closely examine the organizational culture surrounding decision making and provide a structure and process to incorporate research and data…

Resource Allocation Strategies in Doctoral/Research University (Extensive) Libraries

ERIC Educational Resources Information Center

Blake Gonzalez, Barbara

2011-01-01

The purpose of this study was to identify and understand the management of resources by library directors at 151 Public and Private Carnegie classified extensive university libraries in an environment of limited funding for higher education. This study examined the following research questions: 1. What resource allocation strategies are used by…

Resource Allocation and Improved Student Performance: Teachers' Perspectives on School Finance Administration.

ERIC Educational Resources Information Center

Rudo, Zena H.

As expectations rise for students to perform at higher levels, the question of how best to support student performance through resources becomes paramount. In determining new ways to better allocate resources, administrators must consider teacher input on what has/has not been effective in supporting increased student performance. Teachers…

Cross-cultural differences in distributive justice: a comparison of Turkey and the U.S.

PubMed

Murphy-Berman, Virginia A; Berman, John J; Cukur, Cem Safak

2012-01-01

When allocators make decisions about distributing resources, they face a dilemma if the expectations for consequences that will flow from particular choices are incongruent with each other. For example, a certain allocation choice might be expected to make an allocator appear warm and likable but unfair. Previous research has found that culture can shape these perceptions and, thus, their congruence or incongruence. The present study further investigated these ideas. Differences between Turkish and U.S. students' perceptions of allocators who distributed resources on the basis of merit vs. need were investigated. Results revealed an allocation dilemma among the U.S. but not among the Turkish students. Specifically, the U.S. students perceived greater incongruence among allocation consequences for both merit and need choices than did the students from Turkey for whom perceptions of allocator's fairness were more aligned with perceptions of allocator's warmth.

Health Resources Priority and Allocations System (HRPAS). Interim final rule.

PubMed

2015-07-17

This interim final rule establishes standards and procedures by which the U.S. Department of Health and Human Services (HHS) may require that certain contracts or orders that promote the national defense be given priority over other contracts or orders. This rule also sets new standards and procedures by which HHS may allocate materials, services, and facilities to promote the national defense. This rule will implement HHS's administration of priorities and allocations actions, and establish the Health Resources Priorities and Allocation System (HRPAS). The HRPAS will cover health resources pursuant to the authority under Section 101(c) of the Defense Production Act as delegated to HHS by Executive Order 13603. Priorities authorities (and other authorities delegated to the Secretary in E.O. 13603, but not covered by this regulation) may be re-delegated by the Secretary. The Secretary retains the authority for allocations.

Are Indirect Benefits Relevant to Health Care Allocation Decisions?

PubMed Central

Du Toit, Jessica; Millum, Joseph

2016-01-01

Abstract When allocating scarce healthcare resources, the expected benefits of alternative allocations matter. But, there are different kinds of benefits. Some are direct benefits to the recipient of the resource such as the health improvements of receiving treatment. Others are indirect benefits to third parties such as the economic gains from having a healthier workforce. This article considers whether only the direct benefits of alternative healthcare resource allocations are relevant to allocation decisions, or whether indirect benefits are relevant too. First, we distinguish different conceptions of direct and indirect benefits and argue that only a recipient conception could be morally relevant. We analyze four arguments for thinking that indirect benefits should not count and argue that none is successful in showing that the indirectness of a benefit is a good reason not to count it. We conclude that direct and indirect benefits should be evaluated in the same way. PMID:27465773

Allocation of Resources to Communication of Research Result Summaries.

PubMed

Richards, Julie E; Bane, Emmi; Fullerton, Stephanie M; Ludman, Evette J; Jarvik, Gail

2016-10-01

Researchers and policymakers recommend communicating summary research results to biobank participants when feasible. To date, however, there have been few explorations of participant preferences for dedicating resources to this activity. Fifteen semi-structured interviews were conducted with participants of a genetic medicine biobank. Participants were interviewed by phone about their motivation for participation, and opinions about the allocation of resources to communicating summary results. De-identified transcripts were used for a directed content analysis. Most biobank participation was altruistic. All participants were not only interested in receiving summary results but also expressed a clear preference for allocating limited funds to conducting additional genetic research. The results suggest that participants have a nuanced view about the allocation of biobank resources to returning summary results, and asking their opinion is a valuable exercise. Researchers may benefit from transparency about research goals and involving biobank participants in decisions about return of summary results.

Curvilinear relationships between resource allocation and life domain-specific interference.

PubMed

Waldrop, Jessica S; Erb, Kaitlyn R; Grawitch, Matthew J

2017-10-01

This study investigated the inherent complexities of the work-life interface (WLI) by examining the relationship between resource allocation (i.e., time and energy dedicated to a particular domain) and perceived interference of individual life domains. Much of the research on the WLI is based on the assumption that a linear pattern best describes the relationship between resource allocation and the interference caused by various life domains; however, this study examined the possibility that curvilinear relationships may be a more appropriate representation. Results indicated that resource allocation is a meaningful predictor of interference, and for many life domains a curvilinear relationship accounts for more variance than a linear one; a breakdown of the sample also revealed this relationship varies by gender. Overall, findings suggest that the nature of the WLI is more individualized and complex than is currently conceptualized in the field. Copyright © 2016 John Wiley & Sons, Ltd.

Proposing integrated Shannon's entropy-inverse data envelopment analysis methods for resource allocation problem under a fuzzy environment

NASA Astrophysics Data System (ADS)

Çakır, Süleyman

2017-10-01

In this study, a two-phase methodology for resource allocation problems under a fuzzy environment is proposed. In the first phase, the imprecise Shannon's entropy method and the acceptability index are suggested, for the first time in the literature, to select input and output variables to be used in the data envelopment analysis (DEA) application. In the second step, an interval inverse DEA model is executed for resource allocation in a short run. In an effort to exemplify the practicality of the proposed fuzzy model, a real case application has been conducted involving 16 cement firms listed in Borsa Istanbul. The results of the case application indicated that the proposed hybrid model is a viable procedure to handle input-output selection and resource allocation problems under fuzzy conditions. The presented methodology can also lend itself to different applications such as multi-criteria decision-making problems.

The social power of regret: the effect of social appraisal and anticipated emotions on fair and unfair allocations in resource dilemmas.

PubMed

van der Schalk, Job; Kuppens, Toon; Bruder, Martin; Manstead, Antony S R

2015-02-01

We investigated how another person's emotions about resource allocation decisions influence observers' resource allocations by influencing the emotions that observers anticipate feeling if they were to act in the same way. Participants were exposed to an exemplar who made a fair or unfair division in an economic game and expressed pride or regret about this decision. Participants then made their own resource allocation decisions. Exemplar regret about acting fairly decreased the incidence of fair behavior (Studies 1A and 1B). Likewise, exemplar regret about acting unfairly increased the incidence of fair behavior (Study 2). The effect of others' emotions on observers' behavior was mediated by the observers' anticipated emotions. We discuss our findings in light of the view that social appraisal and anticipated emotions are important tools for social learning and may contribute to the formation and maintenance of social norms about greed and fairness.

Resource allocation and funding challenges for regional local health departments in Nebraska.

PubMed

Chen, Li-Wu; Jacobson, Janelle; Roberts, Sara; Palm, David

2012-01-01

This study examined the mechanism of resource allocation among member counties and the funding challenges of regional health departments (RHDs) in Nebraska. DESIGN AND STUDY SETTING: In 2009, we conducted a qualitative case study of 2 Nebraska RHDs to gain insight into their experiences of making resource allocation decisions and confronting funding challenges. The 2 RHD sites were selected for this case study on the basis of their heterogeneity in terms of population distribution in member counties. Sixteen semistructured in-person interviews were conducted with RHD directors, staff, and board of health members. Interview data were coded and analyzed using NVivo qualitative analysis software (QSR International [Americas] Inc., Cambridge, MA). Our findings suggested that the directors of RHDs play an integral role in making resource allocation decisions on the basis of community needs, not on a formula or on individual county population size. Interviewees also reported that the size of the vulnerable population served by the RHD had a significant impact on the level of resources for RHD's programs. The RHD's decisions about resource allocation were also dependent on the amount and type of resources received from the state. Interviewees identified inadequacy and instability of funding as the 2 main funding challenges for their RHD. These challenges negatively impacted workforce capacity and the long-term sustainability of some programs. Regional health departments may not benefit from better leveraging resources and building a stronger structural capacity unless the issues of funding inadequacy and instability are addressed. Strategies that can be used by RHDs to address these funding challenges include seeking grants to support programs, leveraging existing resources, and building community partnerships to share resources. Future research is needed to identify RHDs' optimal workforce capacity, required funding level, and potential funding mechanisms.

Supportive and palliative care for metastatic breast cancer: resource allocations in low- and middle-income countries. A Breast Health Global Initiative 2013 consensus statement.

PubMed

Cleary, James; Ddungu, Henry; Distelhorst, Sandra R; Ripamonti, Carla; Rodin, Gary M; Bushnaq, Mohammad A; Clegg-Lamptey, Joe N; Connor, Stephen R; Diwani, Msemo B; Eniu, Alexandru; Harford, Joe B; Kumar, Suresh; Rajagopal, M R; Thompson, Beti; Gralow, Julie R; Anderson, Benjamin O

2013-10-01

Many women diagnosed with breast cancer in low- and middle-income countries (LMICs) present with advanced-stage disease. While cure is not a realistic outcome, site-specific interventions, supportive care, and palliative care can achieve meaningful outcomes and improve quality of life. As part of the 5th Breast Health Global Initiative (BHGI) Global Summit, an expert international panel identified thirteen key resource recommendations for supportive and palliative care for metastatic breast cancer. The recommendations are presented in three resource-stratified tables: health system resource allocations, resource allocations for organ-based metastatic breast cancer, and resource allocations for palliative care. These tables illustrate how health systems can provide supportive and palliative care services for patients at a basic level of available resources, and incrementally add services as more resources become available. The health systems table includes health professional education, patient and family education, palliative care models, and diagnostic testing. The metastatic disease management table provides recommendations for supportive care for bone, brain, liver, lung, and skin metastases as well as bowel obstruction. The third table includes the palliative care recommendations: pain management, and psychosocial and spiritual aspects of care. The panel considered pain management a priority at a basic level of resource allocation and emphasized the need for morphine to be easily available in LMICs. Regular pain assessments and the proper use of pharmacologic and non-pharmacologic interventions are recommended. Basic-level resources for psychosocial and spiritual aspects of care include health professional and patient and family education, as well as patient support, including community-based peer support. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Robust allocation of a defensive budget considering an attacker's private information.

PubMed

Nikoofal, Mohammad E; Zhuang, Jun

2012-05-01

Attackers' private information is one of the main issues in defensive resource allocation games in homeland security. The outcome of a defense resource allocation decision critically depends on the accuracy of estimations about the attacker's attributes. However, terrorists' goals may be unknown to the defender, necessitating robust decisions by the defender. This article develops a robust-optimization game-theoretical model for identifying optimal defense resource allocation strategies for a rational defender facing a strategic attacker while the attacker's valuation of targets, being the most critical attribute of the attacker, is unknown but belongs to bounded distribution-free intervals. To our best knowledge, no previous research has applied robust optimization in homeland security resource allocation when uncertainty is defined in bounded distribution-free intervals. The key features of our model include (1) modeling uncertainty in attackers' attributes, where uncertainty is characterized by bounded intervals; (2) finding the robust-optimization equilibrium for the defender using concepts dealing with budget of uncertainty and price of robustness; and (3) applying the proposed model to real data. © 2011 Society for Risk Analysis.

Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks

NASA Technical Reports Server (NTRS)

Dudukovich, Rachel; Raible, Daniel E.

2016-01-01

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

Resource allocation. The cost of care: two troublesome cases in health care ethics.

PubMed

Armstrong, C R; Whitlock, R

1998-01-01

With the cost of health care rising rapidly, both physicians and administrators regularly face resource allocation decisions. Under these conditions of relative scarcity, the equitable and appropriate distribution of limited resources becomes an ethical as well as a financial issue. Through ethical analysis, physician executives can assist their physician colleagues and fellow administrators to find rationally defensible answers to questions regarding the distribution of limited resources. Six criteria are frequently "weighted in the balance" by ethicists when analyzing whether justice is served in the distribution of a limited resource: need, equality, contribution, ability to pay, effort, and merit. The authors argue that, from an ethical standpoint, the best single criterion upon which one can base an allocation decision is that of merit, defined as the potential to benefit from the investment of additional resources.

LSST Resources for the Community

NASA Astrophysics Data System (ADS)

Jones, R. Lynne

2011-01-01

LSST will generate 100 petabytes of images and 20 petabytes of catalogs, covering 18,000-20,000 square degrees of area sampled every few days, throughout a total of ten years of time -- all publicly available and exquisitely calibrated. The primary access to this data will be through Data Access Centers (DACs). DACs will provide access to catalogs of sources (single detections from individual images) and objects (associations of sources from multiple images). Simple user interfaces or direct SQL queries at the DAC can return user-specified portions of data from catalogs or images. More complex manipulations of the data, such as calculating multi-point correlation functions or creating alternative photo-z measurements on terabyte-scale data, can be completed with the DAC's own resources. Even more data-intensive computations requiring access to large numbers of image pixels on petabyte-scale could also be conducted at the DAC, using compute resources allocated in a similar manner to a TAC. DAC resources will be available to all individuals in member countries or institutes and LSST science collaborations. DACs will also assist investigators with requests for allocations at national facilities such as the Petascale Computing Facility, TeraGrid, and Open Science Grid. Using data on this scale requires new approaches to accessibility and analysis which are being developed through interactions with the LSST Science Collaborations. We are producing simulated images (as might be acquired by LSST) based on models of the universe and generating catalogs from these images (as well as from the base model) using the LSST data management framework in a series of data challenges. The resulting images and catalogs are being made available to the science collaborations to verify the algorithms and develop user interfaces. All LSST software is open source and available online, including preliminary catalog formats. We encourage feedback from the community.

A leader-follower-interactive method for regional water resources management with considering multiple water demands and eco-environmental constraints

NASA Astrophysics Data System (ADS)

Chen, Yizhong; Lu, Hongwei; Li, Jing; Ren, Lixia; He, Li

2017-05-01

This study presents the mathematical formulation and implementations of a synergistic optimization framework based on an understanding of water availability and reliability together with the characteristics of multiple water demands. This framework simultaneously integrates a set of leader-followers-interactive objectives established by different decision makers during the synergistic optimization. The upper-level model (leader's one) determines the optimal pollutants discharge to satisfy the environmental target. The lower-level model (follower's one) accepts the dispatch requirement from the upper-level one and dominates the optimal water-allocation strategy to maximize economic benefits representing the regional authority. The complicated bi-level model significantly improves upon the conventional programming methods through the mutual influence and restriction between the upper- and lower-level decision processes, particularly when limited water resources are available for multiple completing users. To solve the problem, a bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for measuring to what extent the constraints are met and the objective reaches its optima. The capabilities of the proposed model are illustrated through a real-world case study of water resources management system in the district of Fengtai located in Beijing, China. Feasible decisions in association with water resources allocation, wastewater emission and pollutants discharge would be sequentially generated for balancing the objectives subject to the given water-related constraints, which can enable Stakeholders to grasp the inherent conflicts and trade-offs between the environmental and economic interests. The performance of the developed bi-level model is enhanced by comparing with single-level models. Moreover, in consideration of the uncertainty in water demand and availability, sensitivity analysis and policy analysis are employed for identifying their impacts on the final decisions and improving the practical applications.

A heuristic approach to handle capacitated facility location problem evaluated using clustering internal evaluation

NASA Astrophysics Data System (ADS)

Sutanto, G. R.; Kim, S.; Kim, D.; Sutanto, H.

2018-03-01

One of the problems in dealing with capacitated facility location problem (CFLP) is occurred because of the difference between the capacity numbers of facilities and the number of customers that needs to be served. A facility with small capacity may result in uncovered customers. These customers need to be re-allocated to another facility that still has available capacity. Therefore, an approach is proposed to handle CFLP by using k-means clustering algorithm to handle customers’ allocation. And then, if customers’ re-allocation is needed, is decided by the overall average distance between customers and the facilities. This new approach is benchmarked to the existing approach by Liao and Guo which also use k-means clustering algorithm as a base idea to decide the facilities location and customers’ allocation. Both of these approaches are benchmarked by using three clustering evaluation methods with connectedness, compactness, and separations factors.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

NASA Astrophysics Data System (ADS)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Tying Resources to Results: Integrating the Resource Allocation Process into Planning and Management in a Public Two-Year College.

ERIC Educational Resources Information Center

Bers, John A.

A budgetary process that serves a college in an era of expansion is likely to break down when the resource base is reduced and tough-minded decisions about priorities are required. This paper describes a resource allocation system that Gadsden State Junior College developed and tested over a two-year period to respond to fiscal contraction. Key…

National assessment of geologic carbon dioxide storage resources: allocations of assessed areas to Federal lands

USGS Publications Warehouse

Buursink, Marc L.; Cahan, Steven M.; Warwick, Peter D.

2015-01-01

Following the geologic basin-scale assessment of technically accessible carbon dioxide storage resources in onshore areas and State waters of the United States, the U.S. Geological Survey estimated that an area of about 130 million acres (or about 200,000 square miles) of Federal lands overlies these storage resources. Consequently, about 18 percent of the assessed area associated with storage resources is allocated to Federal land management. Assessed areas are allocated to four other general land-ownership categories as follows: State lands about 4.5 percent, Tribal lands about 2.4 percent, private and other lands about 72 percent, and offshore areas about 2.6 percent.

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

PubMed Central

Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

2016-01-01

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. PMID:27916841

75 FR 76975 - 2015 Resource Pool-Sierra Nevada Region

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-10

...The Western Area Power Administration (Western), a Federal power marketing administration of DOE, announces the Final 2015 Resource Pool allocations pursuant to its 2004 Power Marketing Plan (Marketing Plan) for the Sierra Nevada Customer Service Region (SNR). This notice includes a summary of the comments received on Western's proposed 2015 Resource Pool allocations and Western's responses.

The Unconscious Allocation of Cognitive Resources to Task-Relevant and Task-Irrelevant Thoughts

ERIC Educational Resources Information Center

Kuldas, Seffetullah; Hashim, Shahabuddin; Ismail, Hairul Nizam; Samsudin, Mohd Ali; Bakar, Zainudin Abu

2014-01-01

Conscious allocation of cognitive resources to task-relevant thoughts is necessary for learning. However, task-irrelevant thoughts often associated with fear of failure can enter the mind and interfere with learning. Effects like this prompt the question of whether or not learners consciously shift their cognitive resources from task-relevant to…

Introducing priority setting and resource allocation in home and community care programs.

PubMed

Urquhart, Bonnie; Mitton, Craig; Peacock, Stuart

2008-01-01

To use evidence from research to identify and implement priority setting and resource allocation that incorporates both ethical practices and economic principles. Program budgeting and marginal analysis (PBMA) is based on two key economic principles: opportunity cost (i.e. doing one thing instead of another) and the margin (i.e. resource allocation should result in maximum benefit for available resources). An ethical framework for priority setting and resource allocation known as Accountability for Reasonableness (A4R) focuses on making sure that resource allocations are based on a fair decision-making process. It includes the following four conditions: publicity; relevance; appeals; and enforcement. More recent literature on the topic suggests that a fifth condition, that of empowerment, should be added to the Framework. The 2007-08 operating budget for Home and Community Care, excluding the residential sector, was developed using PBMA and incorporating the A4R conditions. Recommendations developed using PBMA were forwarded to the Executive Committee, approved and implemented for the 2007-08 fiscal year operating budget. In addition there were two projects approved for approximately $200,000. PBMA is an improvement over previous practice. Managers of Home and Community Care are committed to using the process for the 2008-09 fiscal year operating budget and expanding its use to include mental health and addictions services. In addition, managers of public health prevention and promotion services are considering using the process.

Fair Resource Allocation to Health Research: Priority Topics for Bioethics Scholarship.

PubMed

Pratt, Bridget; Hyder, Adnan A

2017-07-01

This article draws attention to the limited amount of scholarship on what constitutes fairness and equity in resource allocation to health research by individual funders. It identifies three key decisions of ethical significance about resource allocation that research funders make regularly and calls for prioritizing scholarship on those topics - namely, how health resources should be fairly apportioned amongst public health and health care delivery versus health research, how health research resources should be fairly allocated between health problems experienced domestically versus other health problems typically experienced by disadvantaged populations outside the funder's country, and how domestic and non-domestic health research funding should be further apportioned to different areas, e.g. types of research and recipients. These three topics should be priorities for bioethics research because their outcomes have a substantial bearing on the achievement of health justice. The proposed agenda aims to move discussion on the ethics of health research funding beyond its current focus on the mismatch between worldwide basic and clinical research investment and the global burden of disease. Individual funders' decision-making on whether and to what extent to allocate resources to non-domestic health research, health systems research, research on the social determinants of health, capacity development, and recipients in certain countries should also be the focus of ethical scrutiny. © 2017 John Wiley & Sons Ltd.

Trade-offs between reproductive allocation and storage in species of Oenothera L. (Onagraceae) native to Argentina

NASA Astrophysics Data System (ADS)

Vilela, Alejandra; Cariaga, Rodrigo; González-Paleo, Luciana; Ravetta, Damián

2008-01-01

A trade-off between reproduction and survival arises because current reproduction diminishes levels of a limiting resource such that less can be placed in storage organs for the survival of an organism during the unfavorable season. Oenothera is a particularly suited genus for studying those kind of trade-offs because it contains species with different life-history strategies (annual, biennial and perennial). Since allocation to leaves is a major factor associated with changes in life-history, here we tested the hypothesis that Oenothera leaf attributes would affect plant reproductive effort and therefore, root reserves. We selected two groups of taxa differing in their leaf area ratio (low- and high-LAR) and we compared their pattern of resource allocation to growth, reproduction and storage. Path analysis confirmed our hypothesis that LAR is the most important variable in explaining variation in allocation to reproduction or storage. The group with high allocation to leaves assigned resources preferentially to storage while the other group allocated more resources to reproduction, as predicted. A trade-off between reproduction and storage was only confirmed for the high-LAR group. The low-LAR group showed the life-history tactic of annual plants, while the high-LAR group exhibited a strategy generally associated with perenniality.

Algorithm Optimally Allocates Actuation of a Spacecraft

NASA Technical Reports Server (NTRS)

Motaghedi, Shi

2007-01-01

A report presents an algorithm that solves the following problem: Allocate the force and/or torque to be exerted by each thruster and reaction-wheel assembly on a spacecraft for best performance, defined as minimizing the error between (1) the total force and torque commanded by the spacecraft control system and (2) the total of forces and torques actually exerted by all the thrusters and reaction wheels. The algorithm incorporates the matrix vector relationship between (1) the total applied force and torque and (2) the individual actuator force and torque values. It takes account of such constraints as lower and upper limits on the force or torque that can be applied by a given actuator. The algorithm divides the aforementioned problem into two optimization problems that it solves sequentially. These problems are of a type, known in the art as semi-definite programming problems, that involve linear matrix inequalities. The algorithm incorporates, as sub-algorithms, prior algorithms that solve such optimization problems very efficiently. The algorithm affords the additional advantage that the solution requires the minimum rate of consumption of fuel for the given best performance.

Resource allocation in public health practice: a national survey of local public health officials.

PubMed

Baum, Nancy M; DesRoches, Catherine; Campbell, Eric G; Goold, Susan Dorr

2011-01-01

The purpose of this study was to gain an empirical understanding of the types of allocation decisions local health officials (LHOs) make and the factors that influence those allocation decisions. We conducted a national survey of LHOs in the United States in 2008 to 2009. The sample was stratified by the size of the population served by the department. We merged our data with data from the 2008 National Association of County and City Health Officials Profile survey. Descriptive statistics were generated using weighted data. Our final sample size was 608 respondents, with an average of 10 years experience. The LHOs reported little shifting of resources among population groups but greater capacity to redirect staffing time. Less than half of LHOs reported using economic analyses or conducting needs assessments when setting priorities. Having sole provider status in a community strongly influenced LHOs' allocation decisions. In addition, the effectiveness of activities, previous budget allocations, and input from boards of health were influential factors in allocation decisions. Public expectations were moderately to very influential, but direct public input had a low impact on allocation decisions. Survey findings provide a clearer understanding of how LHOs fulfill their obligations as stewards of public health resources and ensure effective activities and access to needed services. It may be useful to assess the value of more structured allocation methods (eg, decision frameworks) in the allocation process. Expanding opportunities for public engagement in priority setting may also be valuable for difficult allocation decisions.

Optimizing 4DCBCT projection allocation to respiratory bins.

PubMed

O'Brien, Ricky T; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J

2014-10-07

4D cone beam computed tomography (4DCBCT) is an emerging image guidance strategy used in radiotherapy where projections acquired during a scan are sorted into respiratory bins based on the respiratory phase or displacement. 4DCBCT reduces the motion blur caused by respiratory motion but increases streaking artefacts due to projection under-sampling as a result of the irregular nature of patient breathing and the binning algorithms used. For displacement binning the streak artefacts are so severe that displacement binning is rarely used clinically. The purpose of this study is to investigate if sharing projections between respiratory bins and adjusting the location of respiratory bins in an optimal manner can reduce or eliminate streak artefacts in 4DCBCT images. We introduce a mathematical optimization framework and a heuristic solution method, which we will call the optimized projection allocation algorithm, to determine where to position the respiratory bins and which projections to source from neighbouring respiratory bins. Five 4DCBCT datasets from three patients were used to reconstruct 4DCBCT images. Projections were sorted into respiratory bins using equispaced, equal density and optimized projection allocation. The standard deviation of the angular separation between projections was used to assess streaking and the consistency of the segmented volume of a fiducial gold marker was used to assess motion blur. The standard deviation of the angular separation between projections using displacement binning and optimized projection allocation was 30%-50% smaller than conventional phase based binning and 59%-76% smaller than conventional displacement binning indicating more uniformly spaced projections and fewer streaking artefacts. The standard deviation in the marker volume was 20%-90% smaller when using optimized projection allocation than using conventional phase based binning suggesting more uniform marker segmentation and less motion blur. Images reconstructed using displacement binning and the optimized projection allocation algorithm were clearer, contained visibly fewer streak artefacts and produced more consistent marker segmentation than those reconstructed with either equispaced or equal-density binning. The optimized projection allocation algorithm significantly improves image quality in 4DCBCT images and provides, for the first time, a method to consistently generate high quality displacement binned 4DCBCT images in clinical applications.

An Evaluation of the WSSC (Weapon System Support Cost) Cost Allocation Algorithms. II. Installation Support.

DTIC Science & Technology

1983-06-01

S XX3OXX, or XX37XX is found. As a result, the following two host-financed tenant support accounts currently will be treated as unit operations costs ... Horngren , Cost Accounting : A Managerial Emphasis, Prentice-Hall Inc., Englewood Cliffs, NJ, 1972. 10. D. B. Levine and J. M. Jondrow, "The...WSSC COST ALLOCATION Technical Report ~ALGORITHMS II: INSTALLATION SUPPORT 6. PERFORMING ORG. REPORT NUMBER 7. AUTHOR( S ) 9. CONTRACT OR GRANT NUMBER

Administrators' Decisions about Resource Allocation

ERIC Educational Resources Information Center

Knight, William E.; Folkins, John W.; Hakel, Milton D.; Kennell, Richard P.

2011-01-01

Do academic administrators make decisions about resource allocation differently depending on the discipline receiving the funding? Does an administrator's academic identity influence these decisions? This study explored those questions with a sample of 1,690 academic administrators at doctoral-research universities. Participants used fictional…

Effects of parental care on resource allocation into immune defense and buccal microbiota in mouthbrooding cichlid fishes.

PubMed

Keller, Isabel S; Bayer, Till; Salzburger, Walter; Roth, Olivia

2018-05-01

Sexual dimorphism is founded upon a resource allocation trade-off between investments in reproduction versus other life-history traits including the immune system. In species with conventional parental care roles, theory predicts that males maximize their lifetime reproductive success by allocating resources toward sexual selection, while females achieve this through prolonging their lifespan. Here, we examine the interrelation between sexual dimorphism and parental care strategies in closely related maternal and biparental mouthbrooding cichlid fishes from East African Lake Tanganyika. We measured cellular immune parameters, examined the relative expression of 28 immune system and life history-related candidate genes and analyzed the microbiota composition in the buccal cavity. According to our predictions, maternal mouthbrooders are more sexually dimorphic in immune parameters than biparental mouthbrooders, which has possibly arisen through a differential resource allocation into parental care versus secondary sexual traits. Biparental mouthbrooders, on the other hand, which share the costs of parental care, feature an upregulated adaptive immune response and stronger antiviral properties, while their inflammation response is reduced. Overall, our results suggest a differential resource allocation trade-off between the two modes of parental investment. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Optimal allocation of resources for suppressing epidemic spreading on networks

NASA Astrophysics Data System (ADS)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Decision maker perceptions of resource allocation processes in Canadian health care organizations: a national survey

PubMed Central

2013-01-01

Background Resource allocation is a key challenge for healthcare decision makers. While several case studies of organizational practice exist, there have been few large-scale cross-organization comparisons. Methods Between January and April 2011, we conducted an on-line survey of senior decision makers within regional health authorities (and closely equivalent organizations) across all Canadian provinces and territories. We received returns from 92 individual managers, from 60 out of 89 organizations in total. The survey inquired about structures, process features, and behaviours related to organization-wide resource allocation decisions. We focus here on three main aspects: type of process, perceived fairness, and overall rating. Results About one-half of respondents indicated that their organization used a formal process for resource allocation, while the others reported that political or historical factors were predominant. Seventy percent (70%) of respondents self-reported that their resource allocation process was fair and just over one-half assessed their process as ‘good’ or ‘very good’. This paper explores these findings in greater detail and assesses them in context of the larger literature. Conclusion Data from this large-scale cross-jurisdictional survey helps to illustrate common challenges and areas of positive performance among Canada’s health system leadership teams. PMID:23819598

Water Market-scale Agricultural Planning: Promoting Competing Water Resource Use Efficiency Through Agro-Economics

NASA Astrophysics Data System (ADS)

Delorit, J. D.; Block, P. J.

2017-12-01

Where strong water rights law and corresponding markets exist as a coupled econo-legal mechanism, water rights holders are permitted to trade allocations to promote economic water resource use efficiency. In locations where hydrologic uncertainty drives the assignment of annual per-water right allocation values by water resource managers, collaborative water resource decision making by water rights holders, specifically those involved in agricultural production, can result in both resource and economic Pareto efficiency. Such is the case in semi-arid North Chile, where interactions between representative farmer groups, treated as competitive bilateral monopolies, and modeled at water market-scale, can provide both price and water right allocation distribution signals for unregulated, temporary water right leasing markets. For the range of feasible per-water right allocation values, a coupled agricultural-economic model is developed to describe the equilibrium distribution of water, the corresponding market price of water rights and the net surplus generated by collaboration between competing agricultural uses. Further, this research describes a per-water right inflection point for allocations where economic efficiency is not possible, and where price negotiation among competing agricultural uses is required. An investigation of the effects of water right supply and demand inequality at the market-scale is completed to characterize optimal market performance under existing water rights law. The broader insights of this research suggest that water rights holders engaged in agriculture can achieve economic benefits from forming crop-type cooperatives and by accurately assessing the economic value of allocation.

Family Resource Allocation after Firstborns Leave Home: Implications for Secondborns' Academic Functioning.

PubMed

Jensen, Alexander C; Whiteman, Shawn D; Bernard, Julia M; McHale, Susan M

2017-09-01

This study assessed secondborn adolescents' perceptions of changes in the allocation of family resources following their firstborn siblings' departure from home after high school, and whether perceived changes were related to changes over 1 year in secondborns' academic functioning. Participants were secondborn siblings (mean age = 16.58, SD = 0.91) from 115 families in which the older sibling had left the family home in the previous year. Allocation of resources was measured via coded qualitative interviews. Most (77%) secondborns reported increases in at least one type of family resource (i.e., parental companionship, attention, material goods), and many reported an increase in multiple types of resources in the year following their older sibling's departure. Consistent with resource dilution theory, perceptions of increases in fathers' companionship, fathers' attention, and mothers' companionship were related to improvements over time in secondborns' academic functioning. © 2015 Family Process Institute.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Allocating resources to large wildland fires: a model with stochastic production rates

Treesearch

Romain Mees; David Strauss

1992-01-01

Wildland fires that grow out of the initial attack phase are responsible for most of the damage and burned area. We model the allocation of fire suppression resources (ground crews, engines, bulldozers, and airdrops) to these large fires. The fireline at a given future time is partitioned into homogeneous segments on the basis of fuel type, available resources, risk,...

Resource Allocation with the Use of the Balanced Scorecard and the Triple Bottom Line in Education

ERIC Educational Resources Information Center

Nguyen, Chi Hong

2007-01-01

In terms of the economic bottom line, effective school leaders are now supposed to pay close attention to two central tasks which involve managing resources and devising operational strategies in their action plans. Taking a postmodern viewpoint, the first part of this paper aims to discuss the significance of resource allocation in education and…

Resource Allocation and Educational Adequacy: Case Studies of School-Level Resource Use in Southern California with Budget Reductions

ERIC Educational Resources Information Center

Hobbs, Alysia Jocelyn

2010-01-01

This study selected a purposeful sample of eight high performing southern California elementary schools which achieved API scores above 900 over a three year period. A review of instructional strategies for each study school during the improvement process and resource allocation patterns was determined. Case studies of each school include…

Within-District Resource Allocation and the Marginal Costs of Providing Equal Educational Opportunity: Evidence from Texas and Ohio

ERIC Educational Resources Information Center

Baker, Bruce D.

2009-01-01

This study explores within-district fiscal resource allocation across elementary schools in Texas and Ohio large city school districts and in their surrounding metropolitan areas. Specifically, I ask whether districts widely reported as achieving greater resource equity through adoption of Weighted Student Funding (WSF) have in fact done so. I…

An Examination of Resource Allocation Strategies That Promote Student Achievement: Case Studies of Rural Elementary Schools in Hawaii

ERIC Educational Resources Information Center

Acopan-Tuasivi, C. K.

2012-01-01

This study presents case studies of rural elementary schools in Hawaii that examine resource allocation strategies that promote student achievement. The combined frame work of the Evidence Based Model (Odden & Picus, 2008) and the 10 Strategies for Doubling Student Performance (Odden, 2009) were utilized to compare actual school resources and…

Resource Allocation Modelling in Vocational Rehabilitation: A Prototype Developed with the Michigan and Rhode Island VR Agencies.

ERIC Educational Resources Information Center

Leff, H. Stephen; Turner, Ralph R.

This report focuses on the use of linear programming models to address the issues of how vocational rehabilitation (VR) resources should be allocated in order to maximize program efficiency within given resource constraints. A general introduction to linear programming models is first presented that describes the major types of models available,…

Personnel Resource Allocation Strategies in a Time of Fiscal Stress: A Gap Analysis of Five Southern California Elementary Schools

ERIC Educational Resources Information Center

Araya, Saba Q.

2013-01-01

As pressure increases to ensure that limited resources are utilized as effectively as possible, funding adequacy remains a priority for all California public schools. The research was conducted through a multi-methods approach of principal interviews, site level resource allocation data, and overall student achievement on state assessments. The…

Educational Resource Allocation at the Elementary Level: A Case Study of One Elementary School District in California

ERIC Educational Resources Information Center

Nguyen, Dominic

2013-01-01

The purpose of this study was to examine the dispersion of human capital resources within one school district in southern California and compare the use of personnel at each school to the desired allocation informed by the district's strategies and staffing formula. The district's resource distribution was also compared to that of the Evidence…

Children's Recognition of Fairness and Others' Welfare in a Resource Allocation Task: Age Related Changes

ERIC Educational Resources Information Center

Rizzo, Michael T.; Elenbaas, Laura; Cooley, Shelby; Killen, Melanie

2016-01-01

The present study investigated age-related changes regarding children's (N = 136) conceptions of fairness and others' welfare in a merit-based resource allocation paradigm. To test whether children at 3- to 5-years-old and 6- to 8-years-old took others' welfare into account when dividing resources, in addition to merit and equality concerns,…

76 FR 21003 - Notice of Intent To Prepare a Programmatic Environmental Impact Statement (EIS) and Possible Land...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-14

... Allocation of Oil Shale and Tar Sands Resources on Lands Administered by the Bureau of Land Management in... to prepare a Programmatic EIS for Allocation of Oil Shale and Tar Sands Resources on Lands... following methods: Web site: http://blm.gov/st5c . Mail: BLM Oil Shale and Tar Sands Resources Leasing...

An Examination of Resource Allocation Strategies and Finance Adequacy: Case Studies of American Samoa Department of Education Secondary Schools

ERIC Educational Resources Information Center

Nikolao-Mutini, Akenese Epifania

2012-01-01

The purpose of this study was to analyze American Samoa Department of Education (ASDE) and collect allocation of resources data and determine how the resources are used to increase student performance among a purposeful sample of three public high schools with similar demographics, challenges, fiscal constraints and funding sources located in the…