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VNS-Based Multi-agent Approach to the Dynamic Vehicle Routing Problem

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Computational Collective Intelligence (ICCCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11683))

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Abstract

The paper focuses on Dynamic Vehicle Routing Problem (DVRP), where customers’ requests arrive dynamically while the process of planning and execution of the routing plan is running. Typically, the dynamic problem increases the complexity of the problem and introduces new challenges while finding the optimal route plan. The main contribution of the paper is to propose a multi-agent approach to the DVRP with efficient VNS-based procedure to periodic re-optimization of static subproblems, including requests, which have already arrived to the system. The results of evaluation of the proposed approach confirmed its practical ability do simulate and efficient solve the DVRP.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Gdynia Maritime University, Morska 83, 81-225, Gdynia, Poland

    Dariusz Barbucha

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  1. Dariusz Barbucha
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Correspondence to Dariusz Barbucha .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. University of Pau and Pays de l’Adour, Pau, France

    Richard Chbeir

  3. University of Pau and Pays de l’Adour, Pau, France

    Ernesto Exposito

  4. University of Pau and Pays de l’Adour, Pau, France

    Philippe Aniorté

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Barbucha, D. (2019). VNS-Based Multi-agent Approach to the Dynamic Vehicle Routing Problem. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11683. Springer, Cham. https://doi.org/10.1007/978-3-030-28377-3_46

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  • DOI: https://doi.org/10.1007/978-3-030-28377-3_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28376-6

  • Online ISBN: 978-3-030-28377-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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