Uçak İniş Probleminin Çizelgelenmesinde Bulanık Küme Temelli Bir Genetik Algoritma Yaklaşımı

Uçak İniş Planlaması (UİP) problemi hem havacılığın hem de hava trafik kontrolünün en önemli bölümlerinden birisidir. Problemin esas amacı, bazı kısıtlar altında ihlal maliyetlerinin minimize edilerek uçakların iniş zamanlarının belirlenmesidir. Problemde, uçakların her biri için yakıt, hava hızı ve maliyet ile ilgili iniş zamanlarına dayalı spefikasyonların olduğu optimum hedefler söz konusudur. İniş zamanı hedefinden sapmalar uçağın ve problemin ihlal maliyetlerinin artmasına neden olmaktadır. Bu çalışmada bulanık küme temelli bir genetik algoritma yaklaşımı UİP problemleri için verilmiştir. 500 uçağın ve 5 pistin bulunduğu bir UİP test problemi önerilen tekniğin kullanılması ve değerlendirilmesi için yöneylem araştırması kütüphanesinden elde edilmiştir. Önerilen algoritma ile elde edilen detaylı sonuçlar literatürde yer alan en iyi sonuçlarla kıyaslanmıştır. Önerilen yöntem uygulandığında elde edilen algoritma sonuçları oldukça rekabetçi ve iyi sonuçlardır.

Anahtar Kelimeler:

Uçak İniş, Planlama, Çizelgeleme, Bulanık Küme, Genetik Algoritma, Genetik Algoritma

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.

Keywords:

Aircraft Landing, Scheduling, Timetabling, Fuzzy Cluster, Genetic Algorithms, Genetic Algorithms,

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