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Genetic algorithm for airline crew scheduling problem using cost-based uniform crossover

 
Disciplina: Computação Evolucionária (ELE2395)
Projeto: -
 
Link Original: http://cat.inist.fr/?aModele=afficheN&cpsidt=16334490
 
Abstract
Airline crew scheduling is a very visible and economically significant problem faced by airline industry. Set partitioning problem (SPP) is a role model to represent & solve airline crew scheduling problem. SPP itself is highly constrained combinatorial optimization problem so no algorithm solves it in polynomial time. In this paper we present a genetic algorithm (GA) using new Cost-based Uniform Crossover (CUC) for solving set partitioning problem efficiently. CUC uses cost of the column information for generating offspring. Performance of GA using CUC is evaluated using 28 real-world airline crew scheduling problems and results are compared with well-known IP optimal solutions & Levine's GA solutions [13].
 



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