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akaturk Akademik ölçüm

Makale detayı · 2017

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

YÖKSİS OpenAlex Açık erişim · gold SJR Q1 JCR Q2 Atıf 20 Yüzdelik 82.1% FWCI 1.08
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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Yazarlar

  1. NİHAN ÇETİN DEMİREL YILDIZ TEKNİK ÜNİVERSİTESİ
  2. MUHAMMET DEVECİ