【作者】 任苹；

【Author】 REN Ping (College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.

【机构】 东北大学信息科学与工程学院；

【摘要】 列车优化调度是一个大规模、复杂的、具有非线性离散变量和多约束的多目标数学优化问题．在优化过程中,考虑了高速旅客列车中途离开时间和整个运行时间等因素．首次将粒子群优化(PSO)技术引入列车优化调度,克服了传统优化方法易陷入局部最优和维数灾难等弊端．通过一个工程实例验证了该算法的可行性和有效性．同时,与现存的列车优化调度方法相比,粒子群优化方法的搜索时间短且优化结果更接近最优解．更多还原

【Abstract】 The train scheduling for high-speed passenger railroad planning is formulated as a multi-objective mathematical optimization problem. In this context, two objectives; the variation of inter-departure times for highspeed trains and the total travel time are considered in the optimization. To overcome the drawbacks of conventional mathematical optimization method in arriving at local optimum and dimension disasters, etc. , it introduces the particle swarm optimization (PSO) technique into the train scheduling for high-speed passenger railroad planning for the first time, from which the supreme scheme is generated. A case on the train scheduling for high-speed passenger railroad planning problem is presented to show the methodology’s feasibility and efficiency, compared with the existing optimal planning methods, the search time of the particle swarm optimization method is shorter and the result is close to the ideal solution, simultaneously.更多还原