基于变异进化的不固定牵引方式双肩回交路机车最优配置算法

A Mutating Evolution Algorithm for Locomotive Diagram with Double Shoulders-Circuit Locomotive Routing by the Mode that Unfixed Traction

建立了不固定牵引方式双肩回交路机车周转图的数学模型,以机车在两折返段和基本段总停留时间最少为目标,设计了求解该机车运转制机车最优配置的一种变异进化算法.该算法根据个体适应度的优劣而对个体进行不同程度的变异,并采用启发式变异和随机变异两种变异策略,不但优秀个体的染色体中优良模式能够最大程度地遗传给子代,而且又保持了子代的多样性,有助于提高算法的优化性能和收敛速度.以某列车运行图为例仿真计算,所求得的机车段内总停留时间和需要的机车数比该运行图分别减少约23.8%和9.8%,并与遗传算法进行了比较.

A mathematical model for double shoulders-circuit locomotive routing by the mode that unfixed traction has been presented and the objective is to minimize the total time for locomotives staying in districts. The optimized schedule has been obtained with a mutating evolution algorithm. The algorithm carries on the varying degree mutate according to the fitness of the individual and uses the heuristic mutation. The stochastic mutation can make the eminent schemas heredity to the filial generation which, from the chromosome of the excellent individuals, maintains the filial multiplicity of the generation. Thereby the algorithm can enhance the optimized capability and the convergence rate. The proposed method has been tested over an actual problem of train diagram. The results show that the total time of locomotives staying in the districts and the required number of locomotives are reduced by about 23.8 % and 9.8 % respectively compared with the genetic algorithm.