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Particle swarm optimisation for truck scheduling problem in cross docking network

Author

Listed:
  • Warisa Wisittipanich
  • Takashi Irohara
  • Piya Hengmeechai

Abstract

In cross docking network, multiple products from multiple origins are transferred by trucks through one or more cross docks. One critical concern is the decision on how to synchronise product transshipment through multiple cross docks to achieve timely shipment. This paper presents a mathematical model of truck scheduling problem in cross docking network in order to minimise makespan. Since the problem is NP-hard, a solution method is developed based on particle swarm optimisation (PSO) with two solution representations: randomised truck solution representation (Ra-SR) and prioritised truck solution representation (Pr-SR). The results show that the PSO-based approach performs well in solving the problem. Both solution representations are proven effective when comparing the solution quality and computational time with optimal results obtained from LINGO. However, the Pr-SR yields superior results to the Ra-SR in terms of solution quality and convergence behaviour for most instances especially in the case of large-size problems.

Suggested Citation

  • Warisa Wisittipanich & Takashi Irohara & Piya Hengmeechai, 2020. "Particle swarm optimisation for truck scheduling problem in cross docking network," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 35(3), pages 345-371.
    • Handle: RePEc:ids:ijisen:v:35:y:2020:i:3:p:345-371
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    Cited by:

    1. Imen Hamdi & Imen Boujneh, 2022. "Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 947-969, September.

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