Turnuva seçim operatörü kullanan bir havai fişek algoritması

Öz

Son on yılda doğa olaylarından esinlenerek çeşitli sürü zekasına dayalı optimizasyon teknikleri geliştirilmiştir. Kabul edilebilir bir sürede optimuma yakın çözümler üretebilen bu teknikler, fen ve sosyal bilimlerdeki birçok problemin çözümünde başarıyla uygulanmıştır.  Havai Fişek Algoritması (HFA), havai fişeklerin patlamalarından esinlenilmiş yeni bir sürü zekası algoritmasıdır. Oldukça yeni sayılabilecek bu teknik, çok çeşitli problemlerde başarılı bir şekilde kullanılmış ve özellikle parçacık sürü optimizasyonu, karınca koloni ve genetik algoritma gibi tekniklere göre daha iyi sonuçlar elde edilmiştir. Elde edilen başarılı sonuçlara rağmen, HFA optimum çözüme ulaşmak için uzun zamana ihtiyaç duymaktadır. Bu hesaplama zamanı yetersizliğini giderebilmek amacıyla bu çalışmada turnuva seçimi kullanan bir HFA önerilmiştir. Turnuva seçme operatörüne sahip HFA’nın başarımı 15 adet nümerik optimizasyon probleminde test edilmiştir. Deneysel sonuçlar önerilen HFA’nın klasik HFA’ya göre hesaplama zamanı ve çözüm kalitesinde önemli performans iyileşmeleri sağladığını göstermiştir.

Anahtar Kelimeler

• Sürü zekası,Optimizasyon teknikleri,Nümerik optimizasyon

A fireworks algorithm using tournament selection operator

Abstract

In recent decade, several nature-inspired swarm intelligence-based optimization techniques have been improved. These techniques, which give solutions close to optimum in an acceptable time, have been applied successfully to solve the problems in science and social sciences. Fireworks Algorithm (FA), inspired by observing fireworks explosion, is a new swarm intelligence algorithm. This relatively new technique has been utilized to tackle diverse problems and obtained better performance than other popular techniques such as particle swarm optimization, ant colony, and genetic algorithm. Despite the good results obtained, FA requires long computation time to achieve the optimum solution. To eliminate long computation time drawback of FA, in this study, a FA using tournament selection is proposed. The performance of the proposed FA, which involves tournament selection operator, is tested on well-known 15 numerical optimization problems. Experimental results reveal that proposed FA has a significant performance improvement in term of computation time and solution quality in comparison with original FA.

Keywords

• Swarm intelligence,Optimization techniques,Numerical optimization

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