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A PSO based algorithm with an efficient optimal split procedure for the multiperiod vehicle routing problem with profit

Author

Listed:
  • Racha El-Hajj

    (Université Libanaise)

  • Rym Nesrine Guibadj

    (Université du Littoral Côte d’Opale)

  • Aziz Moukrim

    (Sorbonne Universités)

  • Mehdi Serairi

    (Sorbonne Universités)

Abstract

The multiperiod vehicle routing problem with profit (mVRPP) is a selective vehicle routing problem where the planning horizon of each vehicle is divided into several periods. The aim of solving mVRPP is to design service itineraries so that the total amount of collected profit is maximized and the travel time limit of each period is respected. This problem arises in many real life applications, as the one encountered in cash-in-transit industry. In this paper, we present a metaheuristic approach based on the particle swarm optimization algorithm (PSO) to solve the mVRPP. Our approach incorporates an efficient optimal split procedure and dedicated local search operators proposed to guarantee high search intensification. Experiments conducted on an mVRPP benchmark show that our algorithm outperforms the state of the art metaheuristic approaches in terms of performance and robustness. Our PSO algorithm determines all the already known optimal solutions within a negligible computational time and finds $$88$$ 88 strict improvements among the $$177$$ 177 instances of the benchmark.

Suggested Citation

  • Racha El-Hajj & Rym Nesrine Guibadj & Aziz Moukrim & Mehdi Serairi, 2020. "A PSO based algorithm with an efficient optimal split procedure for the multiperiod vehicle routing problem with profit," Annals of Operations Research, Springer, vol. 291(1), pages 281-316, August.
    • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-020-03540-9
    DOI: 10.1007/s10479-020-03540-9
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    References listed on IDEAS

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