长江集装箱多式联运路径优化动态规划算法

Dynamic programming algorithm for container multimodal transport path optimization of Yangtze river

考虑不同货流运输需求及其时间窗约束,研究长江集装箱多式联运路径优化问题,以运输总费用最小为目标构建数学模型,提出基于深度优先遍历的两阶段多式联运路径优化动态规划算法。第一阶段通过网络遍历提供所有货流可行路径方案集,作为第二阶段的输入完成多式联运路径优化。算例研究结果表明,动态规划算法可实现模型有效求解,适当调整时间窗约束或班次信息可降低多式联运费用。

Considering the transportation demands of different freight flows and their time window constraints,the container multimodal transport path optimization problem was formulated as a mathematical model with the minimization of the total transportation cost.The two-stage multimodal transport path dynamic programming algorithm based on depth first traversal was designed.The algorithm consisted of two stages.The first stage provided all the feasible path plans of different freight flows through the network traveling,and the second stage solved the best multimodal transport path plan with the input of first stage.Numerical examples show that the dynamic programming algorithm can solve the proposed model effectively,and the multimodal transport cost for each freight flow can be reduced by modifying its time window constraint or the transport shift information appropriately.