Optimal solution accoutrement for crew scheduling problem: An innovative solution approach predicating on a tailor-made DSS

Yılmaz Kaya B., Dağdeviren M.

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, cilt.22, sa.4, ss.1489-1527, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 4
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1142/s0219622022500912
  • Dergi Adı: INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1489-1527
  • Anahtar Kelimeler: Crew scheduling, human factors engineering, integer linear programming, decision support systems, operational management, object oriented efficiency
  • Gazi Üniversitesi Adresli: Evet

Özet

Reducing costs on resource consumption against volatile economic environment and market structures is the main concern and key to leadership as constant concern of all industries. Crew scheduling has vital importance, especially in service sector, to manage the most unmeasurable and imponderable resource and cardinal element, human. Due to its NP-Hard structure, although mathematically modeling it is possible, it is nearly impossible to optimally solve it solely relying on mathematical modeling solution methodologies. This study proposes a tailor-made decision support system (DSS) to derive the optimal solution to crew scheduling problem as integer linear programming (ILP) models. The proposed DSS-based ILP approach was introduced on the optimal solution of a large-scaled real-world airline crew scheduling problem considering 189 daily °ights and 14402 possible weekly routes. Additional computational experiments were performed to prove that the proposed DSS could be used for practical support with agility and e±ciency on variant real-life scheduling decisions.