Hamdi Tolga KAHRAMAN, Sefa ARAS, Yusuf SÖNMEZ, Uğur GÜVENÇ, EYÜP GEDİKLİ

Analysis, test and management of the metaheuristic searching process: an experimental study on SOS

In a search process, getting trapped in a local minimum or jumping the global minimum problems are also one of the biggest problems of meta-heuristic algorithms as in artificial intelligence methods. In this paper, causes of these problems are investigated and novel solution methods are developed. For this purpose, a novel framework has been developed to test and analyze the metaheuristic algorithms. Additionally, analysis and test studies have been carried out for Symbiotic Organisms Search (SOS) Algorithm. The aim of the study is to measure the mimicking a natural ecosystem success of symbiotic operators. Thus, problems in the search process have been discovered and operators' design mistakes have been revealed as a case study of the developed testing and analyzing method. Moreover, ways of realizing a precise neighborhood search (intensification) and getting rid of the local minimum (increasing diversification) have been explored. Important information that enhances the performance of operators in the search process has been achieved through experimental studies. Additionally, it is expected that the new experimental test methods developed and presented in this paper contributes to meta-heuristic algorithms studies for designing and testing.

Meta-Sezgisel Arama Sürecinin Analiz, Test ve Yönetimi: SOS Üzerine Deneysel Bir Çalışma

Bir arama sürecinde, yerel minimum tuzağına düşmek ya da küresel minimum noktasını atlamak tıpkı yapay zeka yöntemlerinde olduğu gibi meta-sezgisel algoritmaların en büyük sorunlarından biridir. Bu çalışmada, bu sorunların nedenleri araştırılmış ve yeni çözüm yöntemleri geliştirilmiştir. Bu amaçla, meta-sezgisel algoritmaları test ve analiz etmek için yeni bir çerçeve geliştirilmiştir. Ayrıca yeni ve güçlü bir meta-sezgisel yöntem olan Simbiyotik Organizmalar Arama (SOS) Algoritması için analiz ve test çalışmaları yapılmıştır. Çalışmanın amaçlarından biri, simbiyotik operatörlerin doğal ekosistem taklit başarısını ölçmektir. Böylece, arama sürecindeki problemler keşfedilmiş ve geliştirilen test ve analiz yönteminin bir örneği olarak operatörlerin tasarım hataları ortaya çıkmıştır. Dahası, kesin bir komşuluk arayışını gerçekleştirme ve yerel minimumdan kurtulma yolları (çeşitliliği arttırmak) araştırılmıştır. Araştırma sürecindeki operatörlerin performansını arttıran önemli bilgiler deneysel çalışmalarla sağlanmıştır. Ayrıca, bu çalışmada geliştirilen ve sunulan yeni deneysel test yöntemlerinin, tasarım ve test için meta-sezgisel algoritma çalışmalarına katkıda bulunması beklenmektedir.

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