Multimodal Transport Logistics Model Based on Carbon Factor and Optimal Path Planning Method

Aiming at the problem of Multiple factors, Strong dynamic and inability to express actual status issues well in the Multimodal transport process, this paper has considered comprehensively the factors of transportation costs, transit costs, quality loss costs, carbon emission costs, refrigeration costs, time penalty costs, and proposes a carbon-based multimodal transport logistics model. Inspired by the biological distributed collaboration mechanism, this paper proposes a Mixed Wild Horse Optimization algorithm by introducing a random walk strategy and a growth iteration strategy into the original algorithm, and proves that the proposed algorithm has greatly improved search accuracy and speed through data experimental comparison. Finally, the proposed algorithm is applied to the logistics and transportation problem of agricultural products in the Yangtze River Delta region. The experimental results show that the mixed wild horse optimization algorithm has certain effectiveness and feasibility in multimodal logistics and transportation problems.