Multiobjective Genetic Algorithm to Solve the Train Crew Scheduling Problem

This paper presents a multiobjective genetic algorithm (MOGA)to solve the train crew pairing problem in railway companies. The proposed MOGA 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 duty time and the duty period can be integrated and considered during the evolutionary process. Experiments show that the proposed MOGA 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.