应急物资多式联运鲁棒路径优化

Robust Path Optimization in Multimodal Transportation of Emergency Materials

为解决灾后应急物资多式联运路径优化问题,考虑到应急物资运输网络的不确定性,针对各种运输方式的发班时刻限制,建立了不确定环境下带班期限制的应急物资多式联运鲁棒路径优化模型。同时考虑到计算机求解的NP-hard(nondeterministic polynomial-hard)问题,设计了大变异遗传算法以及自适应遗传算法进行求解,并通过数值案例,对两种算法的求解结果进行了对比分析。研究结果表明:设计的模型及算法可在不确定环境下快速选择出一条时效性好、鲁棒性强的应急物资调拨路径。

To crack the problem of optimizing the multimodal transportation route of emergency supplies after disasters,a robust path optimization mode with schedule restrictions under uncertain environments was established,in which the uncertainties of the emergency supplies transportation network has been considered,and the dispatch time constraints of various transportation methods were also included.At the same time,since it was difficulty for computers to solve NP-hard,a large mutation genetic algorithm and an adaptive genetic algorithm were designed to solve the problem.And then the results of the two algorithms were compared and analyzed through numerical cases.The results finally reveal that the model and algorithm designed can quickly select a time-efficient and robust emergency material allocation path in an uncertain environment.