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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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 |
_version_ |
1724192727087710208 |