Aircraft LandingScheduling (ALS) problem is one of the most important part of both aviation andair traffic control. The main objective of the problem is determining thelanding time of the aircrafts with minimizing the penalty cost under someconstraints. Each aircraft has an optimum target landing time based on theirspecialties related with fuel, airspeed and cost. Deviations from landing timetargets increase the penalty cost of both the aircraft and the problem. In thispaper, a fuzzy cluster based genetic algorithm approach is given for thesolutions of ALS problems. An ALS benchmark, which contains up to 500 aircraftsand five runways, was obtained from OR–library to execute and evaluate thealgorithm. Computational results of the proposed algorithm are given in detailand compared with the best results in the literature. The algorithm resultsshow that it is very competitive and have good results when applied to theregarding problem.
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