Improved Novel Global Harmony Search Algorithm to Optimize the Timetable Problem of Maglev Train ATO System

Abstract

Study the timetable optimization of the ATO system of medium-speed maglev trains. The optimization goal is considering minimizing the total travel time of passengers, establishing a mathematical model. It is of great significance to improve the operating efficiency of trains, ensure the safe operation of trains, on-time arrival of trains, improve the comfort of the trains and passengers’ satisfaction. In order to solve the problem that the basic harmony search algorithm is premature and easily fall into local optimum, an improved novel global harmony search (INGHS) algorithm is improved to solve the model. First, a new location update strategy is given using the adjustment parameter F. At the same time, in order to avoid blind adjustment of the step size in the late search and effectively adjust the structure of the solution, the definition of the norm is introduced to adjust parameter bw dynamically. Take Maglev trains in different time periods as an example, the feasible and effective of the proposed model and algorithm are proved.