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Application of particle swarm optimisation in collaborative scheduling of logistics and supply chain

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  • Hongli Liu
  • Shuang Yang

Abstract

Traditional logistics and supply chain scheduling often focus on single-objective optimisation and ignore the complexity of multiple objectives, resulting in inefficiency and difficulty in cost control. This paper applies the particle swarm optimisation algorithm (PSO) to the collaborative scheduling of logistics and supply chain to improve transportation efficiency. This paper uses PSO to model logistics and supply chain scheduling problems, studies vehicle routing problems, and comprehensively considers multiple objectives such as transportation cost, inventory cost, and delivery time to optimise logistics transportation routes. Experiments show that after vehicle No. 1 was planned using the PSO algorithm, the transportation time was reduced by 2.1 h, the utilisation rate was as high as 98.2%. This shows that the PSO algorithm has significant advantages in logistics and supply chain collaborative scheduling, can effectively perform multi-objective optimisation, and has fast convergence speed and good stability.

Suggested Citation

  • Hongli Liu & Shuang Yang, 2025. "Application of particle swarm optimisation in collaborative scheduling of logistics and supply chain," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 33(1), pages 67-86.
    • Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:67-86
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