A two-stage approach to the depot shunting driver assignment problem with workload balance considerations

Due to its environmentally sustainable and energy-saving characteristics, railway transportation nowadays plays a fundamental role in delivering passengers and goods. Emerged in the area of transportation planning, the crew (workforce) sizing problem and the crew scheduling problem have been attache...

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Bibliographic Details
Published in:PloS one Vol. 12; no. 7; p. e0181165
Main Authors: Wang, Jiaxi, Gronalt, Manfred, Sun, Yan
Format: Journal Article
Language:English
Published: United States Public Library of Science 13.07.2017
Public Library of Science (PLoS)
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ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Summary:Due to its environmentally sustainable and energy-saving characteristics, railway transportation nowadays plays a fundamental role in delivering passengers and goods. Emerged in the area of transportation planning, the crew (workforce) sizing problem and the crew scheduling problem have been attached great importance by the railway industry and the scientific community. In this paper, we aim to solve the two problems by proposing a novel two-stage optimization approach in the context of the electric multiple units (EMU) depot shunting driver assignment problem. Given a predefined depot shunting schedule, the first stage of the approach focuses on determining an optimal size of shunting drivers. While the second stage is formulated as a bi-objective optimization model, in which we comprehensively consider the objectives of minimizing the total walking distance and maximizing the workload balance. Then we combine the normalized normal constraint method with a modified Pareto filter algorithm to obtain Pareto solutions for the bi-objective optimization problem. Furthermore, we conduct a series of numerical experiments to demonstrate the proposed approach. Based on the computational results, the regression analysis yield a driver size predictor and the sensitivity analysis give some interesting insights that are useful for decision makers.
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Competing Interests: The authors have declared that no competing interests exist.
Conceptualization: JW.Data curation: JW.Formal analysis: JW.Methodology: JW MG.Software: JW.Writing – original draft: JW.Writing – review & editing: MG YS.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0181165