Makale detayı · 2017
Novel search space updating heuristics-based genetic algorithm for optimizing medium-scale airline crew pairing problems
- Yıl
- 2017
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı International Journal of Computational Intelligence Systems
- Katalog eşleşmesi (ISSN) International Journal of Computational Intelligence Systems
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
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.
Konular
Atıflar
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20 atıf
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Yerel katalogda bu makaleye atıf yapan 6 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- A survey of the literature on airline crew scheduling 2018
- Evolutionary algorithms for solving the airline crew pairing problem 2018
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- Crew recovery optimization with deep learning and column generation for sustainable airline operation management 2024
- Crew recovery optimization with deep learning and column generation for sustainable airline operation management 2024