A Genetic Algorithm for Obtaining the Optimal Locomotive Working Diagram with Double-Shoulder Circuit Locomotive Routing by the Mode of Unfixed Traction
HE Fengdao · Zhongguo tiedao kexue · 2007
Locomotive working diagram is a multi-constraint combinatorial optimization problem.A mathematical model is established for double-shoulder circuit locomotive routing by the mode of unfixed traction.The objective is to minimize the total time for locomotives staying in districts,and the optimized schedule is obtained with a genetic algorithm.The abilities of local search,convergence and optimization are raised with the knowledge-based mutation operator and the crossing probability,mutating probability self-adjusted by the fitness of the individual.The proposed method was tested over an actual problem of train working diagram.The results show that compared with actual locomotive working diagram,the total time of locomotives staying in districts and the required number of locomotives is reduced by about 21% and 8.6% respectively.