基于列车能耗与建设成本的重载铁路线路纵断面双目标优化OA

To simultaneously reduce train energy consumption and construction cost in heavy-haul railway vertical alignment optimization,a bi-objective optimization model for heavy-haul railway vertical alignment was established.Mileage and elevation of vertical change points were used as decision variables,while constraints on slope length and gradient were considered.The model aimed to minimize train energy consumption and construction cost.An improved bi-objective particle swarm optimization algorithm was then proposed by integrating the"arena competition"method.The"arena competition"method refined the construction process of the non-dominated solution set,and the global optimal solution was obtained through crowding distance and marginal utility analysis.For performance evaluation,the proposed algorithm was compared with the Exclusion Method using the Inverted Generational Distance(IGD)metric on typical test functions.Finally,the proposed bi-objective optimization model and the improved algorithm were applied to a railway line design case.The results showed that the improved bi-objective particle swarm optimization algorithm based on the"arena competition"method exhibited significantly better performance than the Exclusion Method.When applied to typical test functions,it achieved an IGD value of 0.028,which was 0.052 lower than that of the Exclusion Method,produced 20 Pareto optimal solutions,which was 5 more than that of the Exclusion Method,and required 0.26 s less computational time.Compared with the manually designed scheme,the scheme optimized by the proposed model reduced train energy consumption by 3.44%and construction cost by 22.1%.