Parazitizm Safhası ile Değiştirilmiş Bozkurt Eniyileme Algoritması

Bozkurt Eniyileme Algoritması,vahşi doğadaki bir bozkurt sürüsünün avlanma sürecini taklit eden, doğadan esinlenmiş, sürü zekâsı tabanlı, popüler ve etkili bir metasezgisel eniyileme algoritmasıdır. Algoritma hem teorik hem de gerçek hayat problemlerini çözmek için geniş bir alanda kullanılmaktadır. Metasezgiseller eldeki problem için herhangi bir türev bilgisine ihtiyaç duyulmaması, basitlik ve esneklik gibi avantajları olmasına rağmen yerel en iyi çözümde takılıp kalma, erken yakınsama gibi istenilmeyen özelliklere de sahiptir. Metasezgiseller keşif ve yoğunlaşma özelliklerini dengeli bir şekilde kullanmalıdır. Bu çalışmada Bozkurt Eniyileme Algoritmasının keşif yeteneğini geliştirmek amacıyla "parazitizm" olarak adlandırılan basit bir operatörün eklenmesi önerilmiştir. Parazitizm Simbiyotik Organizmalar Araması algoritmasının bir safhasını teşkil eder. Değiştirilmiş algoritmanın iki varyantının performansı 13 test problemi kullanılarak orijinal Bozkurt Eniyileme Algoritması ile karşılaştırılmıştır. Elde edilen sonuçlara göre, orijinal sürüme parazitim safhasının eklenmesi algoritma parametrelerinde daha iyi sonuçların üretilmesini sağlamıştır.

Modified Grey Wolf Optimizer with Parasitism Phase

Grey Wolf Optimizer (GWO) is a popular and effective nature-inspired, swarm intelligence based metaheuristic optimization algorithm which imitates the hunting process of a wolf pack in the nature. It has been widely used to solve both theoretical and real life engineering optimization problems. Even though metaheuristics have many advantages such as requiring no derivative information of the problem at hand, simplicity, and flexibility, they also have some drawbacks like trapping local optima, and premature convergence. They should have a proper balance between diversification (exploration) and intensification (exploitation). In this study, inclusion of a simple operator, namely "parasitism", is proposed to improve the performance of GWO by means of exploration. Parasitism is a phase within Symbiotic Organisms Search (SOS) algorithm. The performances of 2 modified versions are compared with the original GWO, using 13 test beds. Results indicate that inclusion of parasitism phase into the original version has produced better results on the parameters of the algorithm.

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