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Rail-Freight Crew Scheduling with a Genetic Algorithm
Khmeleva, Elena; Hopgood, Adrian; Tipi, Lucian et al.
2014In Bramer, Max; Petridis, Miltos (Eds.) Research and Development in Intelligent Systems XXXI
Peer reviewed
 

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Keywords :
Genetic Algorithm; Crew Scheduling; Rail Freight; Scheduling; Chromosome
Abstract :
[en] This article presents a novel genetic algorithm designed for the solution of the Crew Scheduling Problem (CSP) in the rail-freight industry. CSP is the task of assigning drivers to a sequence of train trips while ensuring that no driver’s schedule exceeds the permitted working hours, that each driver starts and finishes their day’s work at the same location, and that no train routes are left without a driver. Real-life CSPs are extremely complex due to the large number of trips, opportunities to use other means of transportation, and numerous government regulations and trade union agreements. CSP is usually modelled as a set-covering problem and solved with linear programming methods. However, the sheer volume of data makes the application of conventional techniques computationally expensive, while existing genetic algorithms often struggle to handle the large number of constraints. A genetic algorithm is presented that overcomes these challenges by using an indirect chromosome representation and decoding procedure. Experiments using real schedules on the UK national rail network show that the algorithm provides an effective solution within a faster timeframe than alternative approaches.
Disciplines :
Production, distribution & supply chain management
Computer science
Author, co-author :
Khmeleva, Elena;  Sheffield Hallam University > Sheffield Business School
Hopgood, Adrian ;  Université de Liège > HEC - Ecole de gestion de l'ULG : Direction générale
Tipi, Lucian;  Sheffield Hallam University > Sheffield Business School
Shahidan, Malihe;  Sheffield Hallam University > Sheffield Business School
Language :
English
Title :
Rail-Freight Crew Scheduling with a Genetic Algorithm
Publication date :
2014
Event name :
AI-2014: 34th SGAI International Conference on Artificial Intelligence
Event organizer :
BCS Specialist Group on Artificial Intelligence
Event place :
Cambridge, United Kingdom
Event date :
09-11 Dec. 2014
Audience :
International
Main work title :
Research and Development in Intelligent Systems XXXI
Main work alternative title :
[en] Incorporating Applications and Innovations in Intelligent Systems XXII
Editor :
Bramer, Max
Petridis, Miltos
Publisher :
Springer
ISBN/EAN :
978-3-319-12069-0
Pages :
211-223
Peer reviewed :
Peer reviewed
Available on ORBi :
since 09 February 2016

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