Improving transport efficiency is challenging for multimodal transport participants to improve cost-effectiveness. This paper proposes to select city nodes and establish a multi-objective fuzzy optimization model with mixed time window constraints to consider customer demand and transportation time uncertainty. T-rex Optimization algorithm (TROA) is used to solve the problem, which efficiently lowers transportation costs and carbon emissions and has higher precision and dependability than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The efficacy of this method is proven using the example of the multimodal transportation network in China’s central-eastern economic zone. These findings provide potential solutions for multimodal transportation aimed at enhancing transportation efficiency.


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    Title :

    Optimization on Multimodal Network Considering Time Window Under Uncertain Demand


    Contributors:
    Bei, Honghan (author) / Lin, Han (author) / Yang, Fangjiao (author) / Li, Xiaolong (author) / Murcio, Roberto (author) / Yang, Tianren (author)


    Publication date :

    2025-08-01


    Size :

    3671858 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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