Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems

Cooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. T...

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Autores principales:	H. D. Yue, Y. Sun
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/bf4fb3b2d0da4b99917fc7608af3c5c2
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id	oai:doaj.org-article:bf4fb3b2d0da4b99917fc7608af3c5c2
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spelling	oai:doaj.org-article:bf4fb3b2d0da4b99917fc7608af3c5c22021-11-08T02:37:11ZCooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems1607-887X10.1155/2021/2653807https://doaj.org/article/bf4fb3b2d0da4b99917fc7608af3c5c22021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2653807https://doaj.org/toc/1607-887XCooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. Therefore, a two-stage decomposition (TSD) method is proposed in this paper to decompose LSGO problems using as few computational resources as possible. In the first stage, to decompose problems using low computational resources, a hybrid-pool differential grouping (HPDG) method is proposed, which contains a hybrid-pool-based detection structure (HPDS) and a unit vector-based perturbation (UVP) strategy. In the second stage, to decompose the fully nonseparable problems, a known information-based dynamic decomposition (KIDD) method is proposed. Analytical methods are used to demonstrate that HPDG has lower decomposition complexity compared to state-of-the-art static decomposition methods. Experiments show that CC with TSD is a competitive algorithm for solving LSGO problems.H. D. YueY. SunHindawi LimitedarticleMathematicsQA1-939ENDiscrete Dynamics in Nature and Society, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mathematics QA1-939
spellingShingle	Mathematics QA1-939 H. D. Yue Y. Sun Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
description	Cooperative coevolution (CC) is an effective framework for solving large-scale global optimization (LSGO) problems. However, CC with static decomposition method is ineffective for fully nonseparable problems, and CC with dynamic decomposition method to decompose problems is computationally costly. Therefore, a two-stage decomposition (TSD) method is proposed in this paper to decompose LSGO problems using as few computational resources as possible. In the first stage, to decompose problems using low computational resources, a hybrid-pool differential grouping (HPDG) method is proposed, which contains a hybrid-pool-based detection structure (HPDS) and a unit vector-based perturbation (UVP) strategy. In the second stage, to decompose the fully nonseparable problems, a known information-based dynamic decomposition (KIDD) method is proposed. Analytical methods are used to demonstrate that HPDG has lower decomposition complexity compared to state-of-the-art static decomposition methods. Experiments show that CC with TSD is a competitive algorithm for solving LSGO problems.
format	article
author	H. D. Yue Y. Sun
author_facet	H. D. Yue Y. Sun
author_sort	H. D. Yue
title	Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
title_short	Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
title_full	Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
title_fullStr	Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
title_full_unstemmed	Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems
title_sort	cooperative coevolution with two-stage decomposition for large-scale global optimization problems
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/bf4fb3b2d0da4b99917fc7608af3c5c2
work_keys_str_mv	AT hdyue cooperativecoevolutionwithtwostagedecompositionforlargescaleglobaloptimizationproblems AT ysun cooperativecoevolutionwithtwostagedecompositionforlargescaleglobaloptimizationproblems
_version_	1718443035448049664

Cooperative Coevolution with Two-Stage Decomposition for Large-Scale Global Optimization Problems

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