Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25101
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: An estimation of distribution algorithm for public transport driver scheduling
Authors: Shen, Yindong
Li, Jingpeng
Peng, Kunkun
Contact Email: jli@cs.stir.ac.uk
Keywords: metaheuristics
estimation of distribution algorithm
EDA
Bayesian networks
driver scheduling
public transport
legal driver shifts
Issue Date: 2017
Citation: Shen Y, Li J & Peng K (2017) An estimation of distribution algorithm for public transport driver scheduling, International Journal of Operational Research, 28 (2), pp. 245-262.
Abstract: Public transport driver scheduling is a process of selecting a set of duties for the drivers of vehicles to form a number of legal driver shifts. The problem usually has two objectives which are minimising both the total number of shifts and the total shift cost, while taking into account some constraints related to labour and company rules. A commonly used approach is firstly to generate a large set of feasible shifts by domain-specific heuristics, and then to select a subset to form the final schedule by an integer programming method. This paper presents an estimation of distribution algorithm (EDA) to deal with the subset selection problem which is NP-hard. To obtain a candidate schedules, the EDA applies a number of rules, with each rule corresponding to a particular way of selecting a shift. Computational results from some real-world instances of drive scheduling demonstrate the availability of this approach.
DOI Link: http://dx.doi.org/10.1504/IJOR.2017.081483
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