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

Panagiotis Kalatzantonakis (), Angelo Sifaleras () and Nikolaos Samaras ()
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Panagiotis Kalatzantonakis: University of Macedonia
Angelo Sifaleras: University of Macedonia
Nikolaos Samaras: University of Macedonia

Journal of Global Optimization, 2020, vol. 78, issue 2, No 5, 327-348

Abstract: 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.

Keywords: Variable neighborhood search; Parallel computing; Vehicle routing problem; Self-adaptive mechanism (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10898-019-00866-y

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