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Computational Intelligence and Neuroscience
Volume 2016 (2016), Article ID 5804626, 11 pages
http://dx.doi.org/10.1155/2016/5804626
Research Article

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2Department of Transportation Science, KTH Royal Institute of Technology, Teknikringen 10, 10044 Stockholm, Sweden

Received 29 February 2016; Revised 2 May 2016; Accepted 9 May 2016

Academic Editor: Christian W. Dawson

Copyright © 2016 Jiaxi Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality.