Optimizing airline crew scheduling using biased randomization: a case study

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Date
2016Version
Acceso abierto / Sarbide irekia
Type
Contribución a congreso / Biltzarrerako ekarpena
Version
Versión aceptada / Onetsi den bertsioa
Impact
|
10.1007/978-3-319-44636-3_31
Abstract
Various complex decision making problems are related to airline
planning. In the competitive airline industry, ecient crew scheduling
is hereby of major practical importance. This paper presents a metaheuristic
approach based on biased randomization to tackle the challenging
Crew Pairing Problem (CPP). The objective of the CPP is the
establishment of
ight pairings allowing for cost minimiz ...
[++]
Various complex decision making problems are related to airline
planning. In the competitive airline industry, ecient crew scheduling
is hereby of major practical importance. This paper presents a metaheuristic
approach based on biased randomization to tackle the challenging
Crew Pairing Problem (CPP). The objective of the CPP is the
establishment of
ight pairings allowing for cost minimizing crew-
ight
assignments. Experiments are done using a real-life case with dierent
constraints. The results show that our easy-to-use and fast algorithm
reduces overall crew
ying times and the necessary number of accompanying
crews compared to the pairings currently applied by the company. [--]
Subject
Biased randomization,
Airline planning,
Metaheuristics,
Crew pairing problem,
Crew scheduling
Publisher
Springer
Published in
Luaces, O.; Gámez, J. A.; Barrenechea, E.; Troncoso, A.; Galar, M.; Quintián, H.; Corchado, E. (Eds.). Advances in Artificial Intelligence: 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016: proceedings. Berlín: Springer; 2016. p.331-340 978-3-319-44635-6
Departament
Universidad Pública de Navarra. Departamento de Estadística e Investigación Operativa /
Nafarroako Unibertsitate Publikoa. Estatistika eta Ikerketa Operatiboa Saila