Muhammet Deveci

Evolutionary algorithms for solving the airline crew pairing problem

Abstract 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.

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

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.

A survey of the literature on airline crew scheduling

Abstract As the airline industry is ever expanding, companies are increasing their fleet sizes to obtain greater market shares. Moreover, as the airlines seek more growth, the complexity and size of the airline crew scheduling problem, which is one of the major planning problems in the industry, is also increasing. For this reason, companies dedicate resources to solve this problem, and lease software at great expense from external sources. Rigorous mathematical models and algorithms are used in solving these problems. This paper presents a survey of airline crew scheduling problems, and their proposed solutions from the literature. As a conclusion, prospective studies will be proposed and discussed with the aim of developing better solutions for airline crew scheduling problems in the future.