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Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm
KTH, School of Architecture and the Built Environment (ABE), Transport Science.ORCID iD: 0000-0002-1375-9054
2016 (English)In: Computational Intelligence and Neuroscience, ISSN 1687-5265, E-ISSN 1687-5273, 5804626Article in journal (Refereed) Published
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Abstract [en]

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.

Place, publisher, year, edition, pages
2016. 5804626
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-190526DOI: 10.1155/2016/5804626ISI: 000379462300001Scopus ID: 2-s2.0-84982852230OAI: oai:DiVA.org:kth-190526DiVA: diva2:953090
Note

QC 20160816

Available from: 2016-08-16 Created: 2016-08-12 Last updated: 2016-08-16Bibliographically approved

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