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借助于遗传算法的求解功能和特点,将客运专线旅客列车开行方案优化问题描述为对列车运行网络客流分配的寻优。最优的列车开行方案对应于最优的客流分配方案。首先,针对任意的列车开行方案,构建费用—容量运行网络,并通过该网络的最小费用流描述最优客流分配方案,用运行网络中客流分配的最小费用作为个体适应值函数;而后,考虑到网络中列车保本定员限制所产生大量不可行个体的优良遗传信息,设计出求解直线型客运专线单方向旅客列车开行方案优化问题的协同对称群体交叉遗传算法,并进一步将其推广到网状客运专线上。研究发现:可以将开行方案编码的个体描述为含有阶跃容量限制的费用—容量网络,个体的适应值对应于该网络的最小费用流;在非能力过剩网络中,不会出现违反阶跃容量限制的可行流,并且可以通过控制网络容量,避免产生固定费用和负费用。
With the help of the function and characteristic of genetic algorithm, this paper describes the optimization of passenger train line planning in passenger dedicated line as the optimization of passenger flow distribution in train running network. The optimal train operation plan corresponds to the optimal passenger flow distribution plan. Firstly, a cost-capacity operation network is constructed for any train operation plan, and the optimal traffic flow distribution scheme is described by the minimum cost flow of the network. The minimum cost of passenger flow distribution in the operation network is taken as a function of individual fitness. Then, In this paper, we design a crossover genetic algorithm to solve the optimization problem of single-direction passenger trains in linear passenger trains, and further extend it to the network passenger dedicated line on. It is found that the individual coding in the open-circuit scheme can be described as a cost-capacity network with step capacity constraints, and the individual adaptation value corresponds to the minimum cost flow of the network. In non-over-capacity networks, no violation of step capacity Limit the flow of feasible, and can control the network capacity, to avoid generating fixed costs and negative costs.