Evolutionary algorithms for solving the airline crew pairing problem

• Published in: Computers & industrial engineering Vol. 115; pp. 389 - 406
• Main Authors: Deveci, Muhammet, Demirel, Nihan Çetin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2018
• Subjects: Airline crew scheduling; Crew pairing; Genetic algorithm; Heuristics; Memetic algorithm; Set covering; Crew pairing; Memetic algorithm; Set covering; Genetic algorithm; Airline crew scheduling; Heuristics
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2017.11.022

[Display omitted] •Crew pairing problem in airline.•We have applied three evolutionary algorithms.•A hybrid algorithm is developed for an effective study of the recommended algorithm.•The elasticity of these three methods is compared.•The Taguchi method, a statistical experiment design, is used for parameter settings. Solving the airline crew pairing problem (CPP) requires a search to generate a set of minimum-cost crew pairings covering all flight legs, subject to a set of constraints. We propose a solution comprising two consecutive stages: crew pairing generation, followed by an optimisation stage. First, all legal crew pairings are generated with the given flights, and then the best subset of those pairings with minimal cost are chosen via an optimisation, process based on an evolutionary algorithm. This paper investigates the performance of two previously proposed genetic algorithm (GA) variants, and a memetic algorithm (MA) hybridising GA with hill climbing, for solving the CPP. The empirical results across a set of benchmark real-world instances illustrate that the proposed MA is the best performing approach overall.