Abstract
This study proposes a method of inequality-based multiobjective genetic algorithm (MMGA) to solve the aircraft routing problem. The proposed algorithm includes the following features: 1) a method of inequality to confine a genetic algorithm to search a Pareto optimal set in regions of interest with little computing effort; 2) an improved rank-based fitness assignment method to significantly increase the speed of fitness evaluation; and 3) a repairing strategy to relax the infeasible flight schedules to help reduce violations of solutions. The MMGA is successfully applied to solve the aircraft routing problems in a local airline company.
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