摘要
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.
出处
《铁道科学与工程学报》
CAS
CSCD
2010年第4期116-120,共5页
Journal of Railway Science and Engineering
基金
国家自然科学基金资助项目(70671108)
中国博士后科学基金项目(20090460941)
中南大学人文社科基金资助项目
关键词
协同运输
时间不确定
模糊规划
遗传算法
coordination transportation
uncertain time
fuzzy planning
genetic algorithm