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Decision of Multimodal Transportation Scheme Based on Swarm Intelligence

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  • Kai Lei
  • Xiaoning Zhu
  • Jianfei Hou
  • Wencheng Huang

Abstract

In this paper, some basic concepts of multimodal transportation and swarm intelligence were described and reviewed and analyzed related literatures of multimodal transportation scheme decision and swarm intelligence methods application areas. Then, this paper established a multimodal transportation scheme decision optimization mathematical model based on transportation costs, transportation time, and transportation risks, explained relevant parameters and the constraints of the model in detail, and used the weight coefficient to transform the multiobjective optimization problems into a single objective optimization transportation scheme decision problem. Then, this paper is proposed by combining particle swarm optimization algorithm and ant colony algorithm (PSACO) to solve the combinatorial optimization problem of multimodal transportation scheme decision for the first time; this algorithm effectively combines the advantages of particle swarm optimization algorithm and ant colony algorithm. The solution shows that the PSACO algorithm has two algorithms’ advantages and makes up their own problems; PSACO algorithm is better than ant colony algorithm in time efficiency and its accuracy is better than that of the particle swarm optimization algorithm, which is proved to be an effective heuristic algorithm to solve the problem about multimodal transportation scheme decision, and it can provide economical, reasonable, and safe transportation plan reference for the transportation decision makers.

Suggested Citation

  • Kai Lei & Xiaoning Zhu & Jianfei Hou & Wencheng Huang, 2014. "Decision of Multimodal Transportation Scheme Based on Swarm Intelligence," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, April.
    • Handle: RePEc:hin:jnlmpe:932832
    DOI: 10.1155/2014/932832
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    Cited by:

    1. Hongbin Liu & Guopeng Song & Tianyu Liu & Bo Guo, 2022. "Multitask Emergency Logistics Planning under Multimodal Transportation," Mathematics, MDPI, vol. 10(19), pages 1-25, October.
    2. Chunjiao Shao & Haiyan Wang & Meng Yu, 2022. "Multi-Objective Optimization of Customer-Centered Intermodal Freight Routing Problem Based on the Combination of DRSA and NSGA-III," Sustainability, MDPI, vol. 14(5), pages 1-25, March.
    3. Yan Sun & Xinya Li, 2019. "Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncerta," Mathematics, MDPI, vol. 7(8), pages 1-40, August.

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