Next Article in Journal
Commutative Generalized Neutrosophic Ideals in BCK-Algebras
Next Article in Special Issue
Fixed Points Results in Algebras of Split Quaternion and Octonion
Previous Article in Journal
Sharp Bounds on the Higher Order Schwarzian Derivatives for Janowski Classes
Previous Article in Special Issue
Binary Icosahedral Group and 600-Cell
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Symmetry 2018, 10(8), 349; https://doi.org/10.3390/sym10080349

Optimizing the High-Level Maintenance Planning Problem of the Electric Multiple Unit Train Using a Modified Particle Swarm Optimization Algorithm

1
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2
Institute of Computing Technology, China Academy of Railway Sciences, Beijing 100081, China
3
Department of Vehicles, China Railway Shanghai Bureau Group Co., Ltd., Shanghai 200071, China
*
Author to whom correspondence should be addressed.
Received: 17 July 2018 / Revised: 6 August 2018 / Accepted: 17 August 2018 / Published: 19 August 2018
(This article belongs to the Special Issue Discrete Mathematics and Symmetry)
Full-Text   |   PDF [1623 KB, uploaded 20 August 2018]   |  

Abstract

Electric multiple unit (EMU) trains’ high-level maintenance planning is a discrete problem in mathematics. The high-level maintenance process of the EMU trains consumes plenty of time. When the process is undertaken during peak periods of the passenger flow, the transportation demand may not be fully satisfied due to the insufficient supply of trains. In contrast, if the process is undergone in advance, extra costs will be incurred. Based on the practical requirements of high-level maintenance, a 0–1 programming model is proposed. To simplify the description of the model, candidate sets of delivery dates, i.e., time windows, are generated according to the historical data and maintenance regulations. The constraints of the model include maintenance regulations, the passenger transportation demand, and capacities of workshop. The objective function is to minimize the mileage losses of all EMU trains. Moreover, a modified particle swarm algorithm is developed for solving the problem. Finally, a real-world case study of Shanghai Railway is conducted to demonstrate the proposed method. Computational results indicate that the (approximate) optimal solution can be obtained successfully by our method and the proposed method significantly reduces the solution time to 500 s. View Full-Text
Keywords: Electric multiple unit trains; high-level maintenance planning; time window; 0–1 programming model; particle swarm algorithm Electric multiple unit trains; high-level maintenance planning; time window; 0–1 programming model; particle swarm algorithm
Figures

Figure 1

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. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wu, J.; Lin, B.; Wang, H.; Zhang, X.; Wang, Z.; Wang, J. Optimizing the High-Level Maintenance Planning Problem of the Electric Multiple Unit Train Using a Modified Particle Swarm Optimization Algorithm. Symmetry 2018, 10, 349.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Symmetry EISSN 2073-8994 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top