Modified chemical reaction optimization and its application in engineering problems

Chemical Reaction Optimization (CRO) is a simple and efficient evolutionary optimization algorithm by simulating chemical reactions. As far as the current research is concerned, the algorithm has been successfully used for solving a number of real-world optimization tasks. In our paper, a new real e...

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Autores principales:	Shijing Ma, Yunhe Wang, Shouwei Zhang
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	chemical reaction optimization application optimization Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/2f077bf7ac534c32a6d7a96a86014c9d
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spelling	oai:doaj.org-article:2f077bf7ac534c32a6d7a96a86014c9d2021-11-23T01:43:56ZModified chemical reaction optimization and its application in engineering problems10.3934/mbe.20213541551-0018https://doaj.org/article/2f077bf7ac534c32a6d7a96a86014c9d2021-08-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021354?viewType=HTMLhttps://doaj.org/toc/1551-0018Chemical Reaction Optimization (CRO) is a simple and efficient evolutionary optimization algorithm by simulating chemical reactions. As far as the current research is concerned, the algorithm has been successfully used for solving a number of real-world optimization tasks. In our paper, a new real encoded chemical reaction optimization algorithm is proposed to boost the efficiency of the optimization operations in standard chemical reactions optimization algorithm. Inspired by the evolutionary operation of the differential evolution algorithm, an improved search operation mechanism is proposed based on the underlying operation. It is modeled to further explore the search space of the algorithm under the best individuals. Afterwards, to control the perturbation frequency of the search strategy, the modification rate is increased to balance between the exploration ability and mining ability of the algorithm. Meanwhile, we also propose a new population initialization method that incorporates several models to produce high-quality initialized populations. To validate the effectiveness of the algorithm, nine unconstrained optimization algorithms are used as benchmark functions. As observed from the experimental results, it is evident that the proposed algorithm is significantly better than the standard chemical reaction algorithm and other evolutionary optimization algorithms. Then, we also apply the proposed model to address the synthesis problem of two antenna array synthesis. The results also reveal that the proposed algorithm is superior to other approaches from different perspectives.Shijing MaYunhe Wang Shouwei Zhang AIMS Pressarticlechemical reaction optimizationapplicationoptimizationBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 7143-7160 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	chemical reaction optimization application optimization Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	chemical reaction optimization application optimization Biotechnology TP248.13-248.65 Mathematics QA1-939 Shijing Ma Yunhe Wang Shouwei Zhang Modified chemical reaction optimization and its application in engineering problems
description	Chemical Reaction Optimization (CRO) is a simple and efficient evolutionary optimization algorithm by simulating chemical reactions. As far as the current research is concerned, the algorithm has been successfully used for solving a number of real-world optimization tasks. In our paper, a new real encoded chemical reaction optimization algorithm is proposed to boost the efficiency of the optimization operations in standard chemical reactions optimization algorithm. Inspired by the evolutionary operation of the differential evolution algorithm, an improved search operation mechanism is proposed based on the underlying operation. It is modeled to further explore the search space of the algorithm under the best individuals. Afterwards, to control the perturbation frequency of the search strategy, the modification rate is increased to balance between the exploration ability and mining ability of the algorithm. Meanwhile, we also propose a new population initialization method that incorporates several models to produce high-quality initialized populations. To validate the effectiveness of the algorithm, nine unconstrained optimization algorithms are used as benchmark functions. As observed from the experimental results, it is evident that the proposed algorithm is significantly better than the standard chemical reaction algorithm and other evolutionary optimization algorithms. Then, we also apply the proposed model to address the synthesis problem of two antenna array synthesis. The results also reveal that the proposed algorithm is superior to other approaches from different perspectives.
format	article
author	Shijing Ma Yunhe Wang Shouwei Zhang
author_facet	Shijing Ma Yunhe Wang Shouwei Zhang
author_sort	Shijing Ma
title	Modified chemical reaction optimization and its application in engineering problems
title_short	Modified chemical reaction optimization and its application in engineering problems
title_full	Modified chemical reaction optimization and its application in engineering problems
title_fullStr	Modified chemical reaction optimization and its application in engineering problems
title_full_unstemmed	Modified chemical reaction optimization and its application in engineering problems
title_sort	modified chemical reaction optimization and its application in engineering problems
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/2f077bf7ac534c32a6d7a96a86014c9d
work_keys_str_mv	AT shijingma modifiedchemicalreactionoptimizationanditsapplicationinengineeringproblems AT yunhewang modifiedchemicalreactionoptimizationanditsapplicationinengineeringproblems AT shouweizhang modifiedchemicalreactionoptimizationanditsapplicationinengineeringproblems
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Modified chemical reaction optimization and its application in engineering problems

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