用改进的遗传算法求解危险货物零担运输多目标配装问题

The Improved Genetic Algorithm for Multi-subject Loading Allocation of Dangerous Goods in Piece Transportation

危险货物零担运输配装问题是铁路部门复杂而急需解决的实际问题.给出了多目标的数学规划模型,先对待装货物进行预处理,然后运用自适应的遗传算法对问题进行了求解,该算法中自适应杂交变异概率的应用提高了收敛速度.最后通过实例证明了该方法的可行性和有效性.

Loading allocation of dangerous goods in piece transportation has been a complicated and urgent problem with which railway department must deal. This paper presents a multi-objective mathematical programming model for the loading allocation problem. At first, pre-treatment procedure of cargo be loaded are designed using the model, then the solution of the problem given by self-fitted Genetic Algorithm. The adaptive crossover and mutation probability can improve the convergence rate of Genetic Algorithm using the model. Finally, we prove the feasibility and effectiveness of the method from example analysis.