Dynamic size-based multiobjective genetic algorithm to solve the crew pairing problem

This paper presents a dynamic size-based multiobjective genetic algorithm (DSMGA) to solve the crew pairing problem in airline companies. The proposed DSMGA has several features, such as 1) A permutation-based model is proposed rather than the 0-1 set partition model. 2) Instead of pre-assigning a fixed group number of crewmembers, the proposed method can determine it by performing the evolutionary process. 3) The crossover and mutation operators are enhanced so that the flying time and the flight duty period can be integrated and considered during the evolutionary process. Experiments show that the proposed DSMGA can find out optimal solution with exact group number of crewmembers instead of pre-assigning it so that the effective and efficient crew pairing can be yielded.