Analysis, Test and Management of the Meta-Heuristic Searching Process: An Experimental Study on SOS

Year 2020, Volume: 23 Issue: 2, 445 - 455, 01.06.2020

Hamdi Tolga Kahraman Sefa Aras Yusuf Sönmez Uğur Güvenç Eyüp Gedikli

https://doi.org/10.2339/politeknik.548717

Abstract

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 meta-heuristic
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.

Keywords

Symbiotic organisms search, benchmark problem, algorithm analyze, intensification, diversification

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