Marco Antonio M. Carvalho,  André Gustavo dos Santos,  Geraldo Robson Mateus. 

This paper describes the use of genetic algorithms on a crew scheduling problem, more specifically in one of its phases, where a multiobjective set covering problem is used to choose the best set of duties in order to cover several trips. We show the importance of using multiobjective at this context, and describe some ideas incorporated to the classic genetic algorithm. The results confirm that these ideas increase the performance of the genetic algorithm, resulting in better quality and more distributed paretooptimal solution. We also compare the algorithm to other metaheuristics.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2005/034.pdf

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