Selection Based on Colony Fitness for Differential Evolution

Differential evolution (DE) is a competitive and reliable computing technique for continuous optimization. A diversity-based selection has been proved to be valid to improve the performance of DE. However, further study can be done. In this paper, we propose two versions of colony fitness, fitness w...

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Main Authors: Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8558697/
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spelling doaj-16c8461a605c414fbe1c18fb2c139e682021-03-29T21:30:28ZengIEEEIEEE Access2169-35362018-01-016783337834110.1109/ACCESS.2018.28849828558697Selection Based on Colony Fitness for Differential EvolutionZi Ming0https://orcid.org/0000-0002-8323-0922Yang Li1Shijie Peng2https://orcid.org/0000-0002-8287-403XXuechao Wu3Jinyi Guo4School of Economics and Management, China University of Geosciences, Wuhan, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, China4Hubei Post and Telecommunications Planning and Design Co., Ltd, Wuhan, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, ChinaDifferential evolution (DE) is a competitive and reliable computing technique for continuous optimization. A diversity-based selection has been proved to be valid to improve the performance of DE. However, further study can be done. In this paper, we propose two versions of colony fitness, fitness with the consideration of diversity information. Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of the-art DE algorithm. Our experiments are based on the 2005 Congress on Evolutionary Computation and the 2014 Congress on Evolutionary Computation benchmark functions. Experimental results show that our modification on algorithms leads to significantly better solutions than before.https://ieeexplore.ieee.org/document/8558697/Colony fitnessdifferential evolutiondiversityselection
collection DOAJ
language English
format Article
sources DOAJ
author Zi Ming
Yang Li
Shijie Peng
Xuechao Wu
Jinyi Guo
spellingShingle Zi Ming
Yang Li
Shijie Peng
Xuechao Wu
Jinyi Guo
Selection Based on Colony Fitness for Differential Evolution
IEEE Access
Colony fitness
differential evolution
diversity
selection
author_facet Zi Ming
Yang Li
Shijie Peng
Xuechao Wu
Jinyi Guo
author_sort Zi Ming
title Selection Based on Colony Fitness for Differential Evolution
title_short Selection Based on Colony Fitness for Differential Evolution
title_full Selection Based on Colony Fitness for Differential Evolution
title_fullStr Selection Based on Colony Fitness for Differential Evolution
title_full_unstemmed Selection Based on Colony Fitness for Differential Evolution
title_sort selection based on colony fitness for differential evolution
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description Differential evolution (DE) is a competitive and reliable computing technique for continuous optimization. A diversity-based selection has been proved to be valid to improve the performance of DE. However, further study can be done. In this paper, we propose two versions of colony fitness, fitness with the consideration of diversity information. Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of the-art DE algorithm. Our experiments are based on the 2005 Congress on Evolutionary Computation and the 2014 Congress on Evolutionary Computation benchmark functions. Experimental results show that our modification on algorithms leads to significantly better solutions than before.
topic Colony fitness
differential evolution
diversity
selection
url https://ieeexplore.ieee.org/document/8558697/
work_keys_str_mv AT ziming selectionbasedoncolonyfitnessfordifferentialevolution
AT yangli selectionbasedoncolonyfitnessfordifferentialevolution
AT shijiepeng selectionbasedoncolonyfitnessfordifferentialevolution
AT xuechaowu selectionbasedoncolonyfitnessfordifferentialevolution
AT jinyiguo selectionbasedoncolonyfitnessfordifferentialevolution
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