Parallel solver for vehicle routing and pickup and delivery problems with time windows based on agent negotiation

Kalina, Petr; Vokřínek, Jiří

doi:10.1109/icsmc.2012.6377958

Cited by 19 publications

(10 citation statements)

References 12 publications

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“…These advantages are high flexibility, adaptability, scalability, and robustness in decentralized systems, which are achieved by problem decomposition and the proactive, reactive, and adap-tive behavior of intelligent agents. Multiagent systems are mature sophisticated technology to implement autonomous industrial processes [25], [26] and they are also used in route planing [27].…”

Section: Related Workmentioning

confidence: 99%

Forecasting Adverse Weather Situations in the Road Network

Tomás

Pla‐Castells

Martínez

et al. 2016

IEEE Trans. Intell. Transport. Syst.

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Registro de acceso restringido Este recurso no está disponible en acceso abierto por política de la editorial. No obstante, se puede acceder al texto completo desde la Universitat Jaume I o si el usuario cuenta con suscripción. Registre d'accés restringit Aquest recurs no està disponible en accés obert per política de l'editorial. No obstant això, es pot accedir al text complet des de la Universitat Jaume I o si l'usuari compta amb subscripció. Restricted access item This item isn't open access because of publisher's policy. The full--text version is only available from Jaume I University or if the user has a running suscription to the publisher's contents.

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Section: Related Workmentioning

confidence: 99%

Forecasting Adverse Weather Situations in the Road Network

Tomás

Pla‐Castells

Martínez

et al. 2016

IEEE Trans. Intell. Transport. Syst.

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“…On the other hand, improvement heuristics modify an initial solution (very often of a low quality) by applying local search moves (thus, by exploring the neighborhood of this solution) [15], [16]. A number of metaheuristics have been adopted for solving rich VRPs throughout the years, including various tabu searches [4], variable neighborhood searches [17], greedy randomized adaptive search procedures, populationbased [18], [19], [20], and agent-based approaches [21], guided ejection searches [22], simulated annealing [16], and more [23].…”

Section: A Solving the Pickup And Delivery With Time Windowsmentioning

confidence: 99%

“…Parallel heuristic algorithms have been explored for solving a bunch of different optimization problems [24], including various VRPs [21], [25]. Co-operative strategies in such parallel heuristic techniques have been discussed and classified in several taxonomies, with the one presented by Crainic et al being the best established [26], which encompasses three dimensions.…”

Section: B Parallel Heuristic Algorithmsmentioning

confidence: 99%

Is Your Parallel Algorithm Correct?

Nalepa

Błocho

2016

Annals of Computer Science and Information Systems

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Verifying the correctness of parallel algorithms is not trivial, and it is usually omitted in the works from the parallel computation field. In this paper, we discuss in detail how to show that a certain parallel algorithm is correct. This process involves proving its safety and liveness. We perform the in-depth analysis of our parallel guided ejection search (P-GES) for the pickup and delivery problem with time windows, which serves as an excellent case study. P-GES was implemented as a distributed algorithm using the Message Passing Interface library with asynchronous communications, and was validated using the well-known Li and Lim's benchmark containing demanding test instances. We already proved the efficacy of this algorithm and showed that it can retrieve very high-quality (quite often better than the world's best at that time) routing schedules.

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“…They are either evaluated on static benchmarks (cf. [4,13]) or by case studies, which are generally performed in cooperation with an industrial partner (cf. [11,12]).…”

Section: Multiagent Systems In Transport Processesmentioning

confidence: 99%

“…The goal of this investigation is to compare the dispAgent system solutions to the best-known solutions. Similarly to [13], we measure the result quality by the following equation:…”

Section: A Benchmark Evaluationmentioning

confidence: 99%

Autonomous and flexible multiagent systems enhance transport logistics

Gath

Herzog

Edelkamp

2014

2014 11th International Conference &Amp; Expo on Emerging Technologies for a Smarter World (CEWIT)

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This paper presents an autonomous multiagent system which optimizes the planning and scheduling of industrial processes using the example of courier and express services. In order to handle the rising demands and to capitalize on the increasing optimization potential in transport logistics, which both result from the consequent integration of industrial processes into the Internet of Things and Services, the presented dispAgent solution ensures a flexible, adaptive, and proactive system behavior. Intelligent, selfishly acting agents represent logistic entities, which communicate and negotiate with each other to optimize the allocation of orders to transport facilities. The system has been developed in cooperation with our industrial partner tiramizoo, which is an expert in courier and express services. In order to determine the quality of the computed solutions, we evaluated the system using an established benchmark set and compared the results to best-known solutions. In addition, we further validated the system's performance by multiple simulations of real-world scenarios relying on data which was provided by our industrial partner. The results show that the system achieves high quality solutions for the benchmark set and outperforms a standard dispatching software product in real-world scenarios.

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Parallel solver for vehicle routing and pickup and delivery problems with time windows based on agent negotiation

Cited by 19 publications

References 12 publications

Forecasting Adverse Weather Situations in the Road Network

Forecasting Adverse Weather Situations in the Road Network

Is Your Parallel Algorithm Correct?

Autonomous and flexible multiagent systems enhance transport logistics

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