Yinelemeli F-Yarış Algoritması ile Yapay Arı Koloni Algoritmasının Kontrol Parametrelerinin Ayarlanması

Year 2021, Volume: 37 Issue: 1, 12 - 25, 28.04.2021

Ömür Şahin Bahriye Baştürk Akay

Abstract

Meta-sezgisel algoritmaların performansını etkileyen en önemli faktörlerden biri kontrol parametrelerinin değerleridir. Doğru kontrol parametrelerinin belirlenmesi algoritmaların performansını önemli ölçüde artırmaktadır. Ancak pek çok durumda bu kontrol parametrelerinin belirlenmesi oldukça maliyetlidir. Bu nedenle kontrol parametrelerinin belirlenebilmesi için çeşitli yöntemler önerilmiştir ve Yinelemeli F-Yarış algoritması en etkin olan yöntemlerdendir. Bu çalışmada, Yinelemeli F-Yarış algoritmasının Yapay Arı Koloni algoritmasının kontrol parametrelerini belirlemedeki başarımı incelenmiştir. Yinelemeli F-Yarış algoritması ile belirlenen kontrol parametreleri kullanılarak elde edilen sonuçlar literatürde önerilen kontrol parametreleri ile elde edilen sonuçlarla kıyaslanmış ve istatistiksel analizler yapılmıştır. Yinelemeli F-Yarış algoritması kullanılarak, belli bir problem setinin tamamını kapsayacak şekilde kontrol parametre seti elde edilmiş ve CEC'2015 problem seti üzerinde literatürdeki kontrol parametrelerinin elde ettiği sonuçlar ile kıyaslanmıştır. Elde edilen sonuçlar, kontrol parametrelerinin Yinelemeli F-Yarış algoritması ile ayarlanmasının hesaplama maliyetini artırmadan algoritmaların performansını artırdığını göstermektedir.

Keywords

Yapay Arı Koloni Algoritması, Yinelemeli F-Yarış, Kontrol Parametre Analizi, CEC'2015, F-Yarış

Thanks

Bu araştırmada yer alan kısmi nümerik hesaplamalar TÜBİTAK ULAKBİM, Yüksek Başarım ve Grid Hesaplama Merkezi'nde (TRUBA kaynaklarında) gerçekleştirilmiştir.

Parameter Tuning of Artificial Bee Colony Algorithm Using Iterative F-Race Algorithm

Abstract

One of the most important factors affecting the performance of meta-heuristic algorithms is control parameters. Determining the correct control parameters significantly increases the performance of the algorithms. However, most of the time, determining these control parameters is very expensive task. Therefore, various methods have been proposed to tune the control parameters and the Iterative F-Race algorithm is one of the most effective methods. In this study, the performance of the Iterative F-Race algorithm in determining the control parameters of the Artificial Bee Colony algorithm was examined. The results obtained using the control parameters determined by the Iterative F-Race algorithm were compared with the results obtained with the control parameters recommended in the literature and statistical analyzes were applied. Using the iterative F-Race algorithm, a control parameter set that covers a certain problem set has been obtained and compared with the results of the control parameters in the literature on the CEC'2015 problem set. The results show that tuning the control parameters with the Iterative F-Race algorithm improves the performance of the algorithms without increasing the computational cost.

Keywords

Artificial Bee Colony Algorithm, Iterative F-Race, Control Parameter Tuning, CEC’2015, F-Race

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