不确定环境下协同运输优化模型及其求解算法

An optimization model for coordination transportation and its solution algorithm under uncertain environment

在分析各种运输方式经济技术特性(速度、费用、运输能力等)的基础上,综合考虑多式联运实际运作过程中,运输时间和换装时间不确定性、换装条件和顾客对对货物到达时间窗的限制等因素,构建了一个时效性多式联运协同优化模型,针对模型的特点设计了相应的遗传算法。最后,给出了一个仿真算例,并分析了时间窗参数变化对最优解的影响,同时将该算法与其他求解方法进行了对比分析,仿真结果表明:遗传算法是解决不确定环境下多式联运协同优化模型行之有效的求解算法。

Based on the analysis of the technical and economical characteristics of transportation modes （such as speed, cost and transport capacity）, this paper presented a fuzzy planning optimization model for multi - modal transportation, in which the factors including the transportation time and transfer time with uncertainty, transfer conditions and time -window demanded by customer were considered. According to the characteristic of the optimization model, the genetic algorithm was investigated to solve the proposed model. In the end, a numerical example was provided to validate the model and algorithm. The influence of the optimization solution with the time - windows parameter change was analyzed. Meanwhile, the comparison among the given genetic algorithm （GA） and other methods was presented on search capability for optimization solution. The simulation result shows that genetic algorithm is valid and effective to solve the optimization model for multi -modal transportation under environment.