International Journal of Computational Intelligence Systems

Volume 10, Issue 1, 2017, Pages 1082 - 1101

Novel search space updating heuristics-based genetic algorithm for optimizing medium-scale airline crew pairing problems

Authors
Nihan Çetin Demirelnihan@yildiz.edu.tr, Muhammet Devecimuhammetdeveci@gmail.com
Department of Industrial Engineering, University of Yildiz Technical, Barbaros Bulvarı 34349 Yildiz, Istanbul, Turkey
Received 27 April 2017, Accepted 5 July 2017, Available Online 20 July 2017.
DOI
10.2991/ijcis.2017.10.1.72How to use a DOI?
Keywords
Airline crew scheduling; Crew pairing; Set-covering; Genetic algorithm; Heuristics
Abstract

This study examines the crew pairing problem, which is one of the most comprehensive problems encountered in airline planning, to generate a set of crew pairings that has minimal cost, covers all flight legs and fulfils legal criteria. In addition, this study examines current research related to crew pairing optimization. The contribution of this study is developing heuristics based on an improved dynamic-based genetic algorithm, a deadhead-minimizing pairing search and a partial solution approach (less-costly alternative pairing search). This study proposes genetic algorithm variants and a memetic algorithm approach. In addition, computational results based on real-world data from a local airline company in Turkey are presented. The results demonstrate that the proposed approach can successfully handle medium sets of crew pairings and generate higher-quality solutions than previous methods.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
10 - 1
Pages
1082 - 1101
Publication Date
2017/07/20
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2017.10.1.72How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Nihan Çetin Demirel
AU  - Muhammet Deveci
PY  - 2017
DA  - 2017/07/20
TI  - Novel search space updating heuristics-based genetic algorithm for optimizing medium-scale airline crew pairing problems
JO  - International Journal of Computational Intelligence Systems
SP  - 1082
EP  - 1101
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2017.10.1.72
DO  - 10.2991/ijcis.2017.10.1.72
ID  - Demirel2017
ER  -