基于组合算法的易腐货物多式联运路径优化

Multi-modal Transportation Routing Optimization of Perishable Goods Based on Combinatorial Algorithm

为解决易腐货物多式联运路径优化问题,考虑时间窗约束,建立一种总成本最低的易腐货物多式联运路径优化模型.因遗传算法全局搜索能力强,禁忌搜索算法依赖初始解与领域结构的特点,设计了遗传-禁忌搜索组合算法,来求解最佳运输方式下的低成本最优路径.为验证多式联运的优势,特举实例将多式联运与单一运输方式进行对比;实例可知,组合算法有较高实用价值,为易腐货物多式联运运营人在今后的路径选择决策上提供参考依据.

In order to solve the multimodal transportation path optimization problem of perishable goods,a multimodal transportation path optimization model with the lowest total cost was established considering the time window constraint.Since genetic algorithm has a strong global search ability,so tabu search algorithm relies on the characteristics of initial solution and domain structure,and a combination algorithm of genetic and tabu search is designed to solve the optimal path with low cost under the optimal transportation mode.In order to verify the advantages of multimodal transport,a particular example is given to compare multimodal transport with single transport mode.The example shows that the combined algorithm has high practical value,which provides reference for perishable goods multimodal transport operators in the future route selection decision.