Optimization Study of Line Planning for High Speed Railway Based on an Improved Multi-Objective Differential Evolution Algorithm

The combination optimization of the train operation plan is an ongoing challenge: while computing power has improved, it is difficult to obtain a complete train operation plan system. With the aim of generating system-optimal operation strategies, a new collaborative optimization method is proposed for line planning problem. Through a set of constraints, the problem is formulated as a two-objective model with the objectives of economic benefits and market effects. An optimization approach with adaptive improvement of control parameters based on the multi-objective differential evolution (MODE) algorithm is proposed to solve the model, and a heuristic algorithm is designed to get a better initial solution. Finally, computational results on benchmark multi-objective problems show that the improvements of the strategies are positive and the optimization result of the improved algorithm has better stability. Meanwhile, based on a numerical example of a practical case study involving a 397-kilometer railway corridor to demonstrate the effectiveness of the proposed model and solution. As the basis of successive decisions, this method can adjust the number of trains according to the passenger flow demand, which greatly saves operating costs.