A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem

Taking inspiration from an organizational evolutionary algorithm for numerical optimization, this paper designs a kind of dynamic population and combining evolutionary operators to form a novel algorithm, a cooperative coevolutionary cuckoo search algorithm (CCCS), for solving both unconstrained, co...

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Main Authors: Hongqing Zheng, Yongquan Zhou
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/912056
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author Hongqing Zheng
Yongquan Zhou
author_facet Hongqing Zheng
Yongquan Zhou
author_sort Hongqing Zheng
collection DOAJ
description Taking inspiration from an organizational evolutionary algorithm for numerical optimization, this paper designs a kind of dynamic population and combining evolutionary operators to form a novel algorithm, a cooperative coevolutionary cuckoo search algorithm (CCCS), for solving both unconstrained, constrained optimization and engineering problems. A population of this algorithm consists of organizations, and an organization consists of dynamic individuals. In experiments, fifteen unconstrained functions, eleven constrained functions, and two engineering design problems are used to validate the performance of CCCS, and thorough comparisons are made between the CCCS and the existing approaches. The results show that the CCCS obtains good performance in the solution quality. Moreover, for the constrained problems, the good performance is obtained by only incorporating a simple constraint handling technique into the CCCS. The results show that the CCCS is quite robust and easy to use.
format Article
id doaj-art-4c5cd83a9c7f41a78365dac19d9463dd
institution Kabale University
issn 1110-757X
1687-0042
language English
publishDate 2013-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-4c5cd83a9c7f41a78365dac19d9463dd2025-02-03T01:07:30ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/912056912056A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization ProblemHongqing Zheng0Yongquan Zhou1Guangxi Key Laboratory of Hybrid Computation and Integrated Circuit Design Analysis, Nanning, Guangxi 530006, ChinaGuangxi Key Laboratory of Hybrid Computation and Integrated Circuit Design Analysis, Nanning, Guangxi 530006, ChinaTaking inspiration from an organizational evolutionary algorithm for numerical optimization, this paper designs a kind of dynamic population and combining evolutionary operators to form a novel algorithm, a cooperative coevolutionary cuckoo search algorithm (CCCS), for solving both unconstrained, constrained optimization and engineering problems. A population of this algorithm consists of organizations, and an organization consists of dynamic individuals. In experiments, fifteen unconstrained functions, eleven constrained functions, and two engineering design problems are used to validate the performance of CCCS, and thorough comparisons are made between the CCCS and the existing approaches. The results show that the CCCS obtains good performance in the solution quality. Moreover, for the constrained problems, the good performance is obtained by only incorporating a simple constraint handling technique into the CCCS. The results show that the CCCS is quite robust and easy to use.http://dx.doi.org/10.1155/2013/912056
spellingShingle Hongqing Zheng
Yongquan Zhou
A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
Journal of Applied Mathematics
title A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
title_full A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
title_fullStr A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
title_full_unstemmed A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
title_short A Cooperative Coevolutionary Cuckoo Search Algorithm for Optimization Problem
title_sort cooperative coevolutionary cuckoo search algorithm for optimization problem
url http://dx.doi.org/10.1155/2013/912056
work_keys_str_mv AT hongqingzheng acooperativecoevolutionarycuckoosearchalgorithmforoptimizationproblem
AT yongquanzhou acooperativecoevolutionarycuckoosearchalgorithmforoptimizationproblem
AT hongqingzheng cooperativecoevolutionarycuckoosearchalgorithmforoptimizationproblem
AT yongquanzhou cooperativecoevolutionarycuckoosearchalgorithmforoptimizationproblem