A Fuzzy Cluster Based Genetic Algorithm Approach for the Aircraft Landing Scheduling Problem

Aircraft Landing Scheduling (ALS) problem is one of the most important part of both aviation and air traffic control. The main objective of the problem is determining the landing time of the aircrafts with minimizing the penalty cost under some constraints. Each aircraft has an optimum target landing time based on their specialties related with fuel, airspeed and cost. Deviations from landing time targets increase the penalty cost of both the aircraft and the problem. In this paper, a fuzzy cluster based genetic algorithm approach is given for the solutions of ALS problems. An ALS benchmark, which contains up to 500 aircrafts and five runways, was obtained from OR–library to execute and evaluate the algorithm. Computational results of the proposed algorithm are given in detail and compared with the best results in the literature. The algorithm results show that it is very competitive and have good results when applied to the regarding problem