The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions

Along with the increasing number of nature-inspired algorithms, more and more benchmark functions were also involved in the initial verification experiments. The benchmark functions were introduced to verify the capability of algorithms in optimization, but not all of them could be optimized, becaus...

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Main Authors:	Zheng-Ming Gao, Juan Zhao, Yu-Rong Hu, Hua-Feng Chen
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Access
Subjects:	Nature-inspired algorithm optimization algorithms benchmark functions non-symmetry
Online Access:	https://ieeexplore.ieee.org/document/9497097/

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record_format	Article
spelling	doaj-e79db33e677d4e6d8b6e6fd429871a0b2021-08-09T23:00:37ZengIEEEIEEE Access2169-35362021-01-01910631710633910.1109/ACCESS.2021.31003659497097The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark FunctionsZheng-Ming Gao0https://orcid.org/0000-0003-1566-7134Juan Zhao1Yu-Rong Hu2Hua-Feng Chen3School of Computer Engineering, Jingchu University of Technology, Jingmen, ChinaSchool of Electronics and Information Engineering, Jingchu University of Technology, Jingmen, ChinaDepartment of Science and Technology, Jingchu University of Technology, Jingmen, ChinaSchool of Computer Engineering, Jingchu University of Technology, Jingmen, ChinaAlong with the increasing number of nature-inspired algorithms, more and more benchmark functions were also involved in the initial verification experiments. The benchmark functions were introduced to verify the capability of algorithms in optimization, but not all of them could be optimized, because they were different from each other in dimensionality, separability, scalability, and modality <italic>et.al.</italic>. In this paper, we introduced another property called symmetry or non-symmetry, which should be another embedded characteristic of functions affecting the capability of algorithms in optimization. 67 non-symmetric benchmark functions were collected and 9 popular capability-verified algorithms were introduced in four types of simulation experiments. Experimental results show that most of the non-symmetric algorithms could not be optimized. And none of the algorithms involved could optimize them all. Efforts remain in need of new methods and improvements of nature-inspired algorithms.https://ieeexplore.ieee.org/document/9497097/Nature-inspired algorithmoptimization algorithmsbenchmark functionsnon-symmetry
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Zheng-Ming Gao Juan Zhao Yu-Rong Hu Hua-Feng Chen
spellingShingle	Zheng-Ming Gao Juan Zhao Yu-Rong Hu Hua-Feng Chen The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions IEEE Access Nature-inspired algorithm optimization algorithms benchmark functions non-symmetry
author_facet	Zheng-Ming Gao Juan Zhao Yu-Rong Hu Hua-Feng Chen
author_sort	Zheng-Ming Gao
title	The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions
title_short	The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions
title_full	The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions
title_fullStr	The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions
title_full_unstemmed	The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions
title_sort	challenge for the nature-inspired global optimization algorithms: non-symmetric benchmark functions
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2021-01-01
description	Along with the increasing number of nature-inspired algorithms, more and more benchmark functions were also involved in the initial verification experiments. The benchmark functions were introduced to verify the capability of algorithms in optimization, but not all of them could be optimized, because they were different from each other in dimensionality, separability, scalability, and modality <italic>et.al.</italic>. In this paper, we introduced another property called symmetry or non-symmetry, which should be another embedded characteristic of functions affecting the capability of algorithms in optimization. 67 non-symmetric benchmark functions were collected and 9 popular capability-verified algorithms were introduced in four types of simulation experiments. Experimental results show that most of the non-symmetric algorithms could not be optimized. And none of the algorithms involved could optimize them all. Efforts remain in need of new methods and improvements of nature-inspired algorithms.
topic	Nature-inspired algorithm optimization algorithms benchmark functions non-symmetry
url	https://ieeexplore.ieee.org/document/9497097/
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The Challenge for the Nature-Inspired Global Optimization Algorithms: Non-Symmetric Benchmark Functions

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