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A Multiobjective Large Neighborhood Search for a Vehicle Routing Problem

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Advances in Swarm Intelligence (ICSI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8795))

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Abstract

In this paper, a multiobjective adaptive large neighborhood search is proposed for a vehicle routing problem (VRP) of which the objectives are the total travel time and the cumulative time, i.e., the total arrival time at all customers. It hybrids destroy-repair operators with local search for generating new solutions. An adaptive probabilistic rule based on Pareto dominance is proposed to select a combination of destroy-repair operator. The effectiveness of the proposed algorithm is supported by the experimental study.

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Author information

Authors and Affiliations

  1. The State Key Laboratory for Manufacturing Systems Engineering, Xian Jiaotong University, Xi’an, 710049, China

    Liangjun Ke & Laipeng Zhai

Authors
  1. Liangjun Ke
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  2. Laipeng Zhai
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Computer Science Department, CINVESTAV-IPN, Mexico

    Carlos A. Coello Coello

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Ke, L., Zhai, L. (2014). A Multiobjective Large Neighborhood Search for a Vehicle Routing Problem. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_36

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  • DOI: https://doi.org/10.1007/978-3-319-11897-0_36

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11896-3

  • Online ISBN: 978-3-319-11897-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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