Dual population differential evolution algorithm-based optimization method for periodic train schedule dispatching

Abstract

An optimization problem of train schedule dispatching is a basic problem in the railway industrial field. The invention applies a differential evolution algorithm to the optimization for the periodic train schedule dispatching and relates to two large fields of train dispatching and intelligent calculation. The method utilizes the differential evolution algorithm to optimize departure times of trains of all service lines of a railroad system adopting a periodic departure way, so as to minimize the waiting time of a passenger for transferring in a relay station. According to the invention, dual population-based parameters and operator control mechanism are introduced into the algorithm, which greatly reduces the parameter sensitivity of the algorithm and improves the optimization efficiency and robustness of the algorithm. Taking a Guangzhou subway network and six man-made railway networks as examples for simulation tests, the method is proved to be very effective.

Description

Technical field: [0001] The invention relates to two major fields of train scheduling and intelligent computing, and mainly relates to a periodic train timetable scheduling optimization method based on a dual population differential evolution algorithm. Background technique: [0002] The optimization problem of train schedule scheduling is a basic problem in the field of railway industry. It requires setting the departure and arrival times of trains, so as to avoid conflicts between trains and meet the requirements of passenger safety and speed. Currently, the commonly used methods for setting train timetables include integer programming, branch and bound and other nonlinear techniques. The invention focuses on solving the scheduling problem of periodic train schedules, that is, the trains on each service route depart from the departure station periodically. Currently, periodic train timetable scheduling is widely used in bus, subway and railway systems in many countries, ...

AI Technical Summary

Problems solved by technology

The traditional differential evolution algorithm is sensitive to parameter and operator settings in practical applications, and has shortcomings such as falling into local optimization and slow convergence speed.

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