Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/234
Title: Comparison between SSA and SSO algorithm inspired in the behavior of the social spider for constrained optimization
Authors: Baş, Emine
Ülker, Erkan
Keywords: Constrained Optimization
Heuristic
Social Spider
Spider Web
Ssa
Sso
Evolution Algorithm
Selection
Publisher: SPRINGER
Abstract: The heuristic algorithms are often used to find solutions to real complex world problems. In this paper, the Social Spider Algorithm (SSA) and Social Spider Optimization (SSO) which are heuristic algorithms created upon spider behaviors are considered. Performances of both algorithms are compared with each other from six different items. These are; fitness values of spider population which are obtained in different dimensions, number of candidate solution obtained in each iteration, the best value of candidate solutions obtained in each iteration, the worst value of candidate solutions obtained in each iteration, average fitness value of candidate solutions obtained in each iteration and running time of each iteration. Obtained results of SSA and SSO are applied to the Wilcoxon signed-rank test. Various unimodal, multimodal, and hybrid standard benchmark functions are studied to compare each other with the performance of SSO and SSA. Using these benchmark functions, performances of SSO and SSA are compared with well-known evolutionary and recently developed methods in the literature. Obtained results show that both heuristic algorithms have advantages to another from different aspects. Also, according to other algorithms have good performance.
URI: https://doi.org/10.1007/s10462-021-10035-x
https://hdl.handle.net/20.500.13091/234
ISSN: 0269-2821
1573-7462
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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