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An estimation of distribution algorithm for public transport driver scheduling

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.

Keywords
metaheuristics; estimation of distribution algorithm; EDA; Bayesian networks; driver scheduling; public transport; legal driver shifts

StatusPublished
AuthorsShen Yindong, Li Jingpeng, Peng Kunkun
Publication date2017
Publication date online12/12/2016
Date accepted by journal28/06/2015
PublisherInderscience
ISSN 1745-7645
LanguageEnglish

Journal
International Journal of Operational Research: Volume 28, Issue 2 (2017)

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