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Cooperative versus non-cooperative parallel variable neighborhood search strategies: a case study on the capacitated vehicle routing problem

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Abstract

The capacitated vehicle routing problem (CVRP) is a well-known NP-hard combinatorial optimization problem with numerous real-world applications in logistics. In this work, we present a literature review with recent successful parallel implementations of variable neighborhood search regarding different variants of vehicle routing problems. We conduct an experimental study for the CVRP using well-known benchmark instances, and we present and investigate three parallelization strategies that coordinate the communication of the multiple processors. We experimentally evaluate a non-cooperative and two novel cooperation models, the managed cooperative and the parameterized cooperative strategies. Our results constitute a first proof-of-concept for the benefits of this new self-adaptive parameterized cooperative approach, especially in computationally hard instances.

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Authors and Affiliations

  1. Department of Applied Informatics, School of Information Sciences, University of Macedonia, 156 Egnatias Str., 54636, Thessaloníki, Greece

    Panagiotis Kalatzantonakis, Angelo Sifaleras & Nikolaos Samaras

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  1. Panagiotis Kalatzantonakis
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  2. Angelo Sifaleras
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  3. Nikolaos Samaras
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Correspondence to Angelo Sifaleras.

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Kalatzantonakis, P., Sifaleras, A. & Samaras, N. Cooperative versus non-cooperative parallel variable neighborhood search strategies: a case study on the capacitated vehicle routing problem. J Glob Optim 78, 327–348 (2020). https://doi.org/10.1007/s10898-019-00866-y

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