An enhanced artificial bee colony algorithm based on fitness weighted search strategy

Artificial Bee Colony (ABC) algorithm is a meta-heuristic algorithm, is inspired by the bee’s food search behaviour based on swarm intelligence. Successful applications were performed on many optimization problems using this algorithm rising in popularity over the past few years. The update mechanis...

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Autor principal: Yuksel Celik
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Lenguaje:EN
Publicado: Taylor & Francis Group 2021
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Acceso en línea:https://doaj.org/article/61755681e4d042e0802e734d9c33d8f0
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spelling oai:doaj.org-article:61755681e4d042e0802e734d9c33d8f02021-11-04T15:00:41ZAn enhanced artificial bee colony algorithm based on fitness weighted search strategy0005-11441848-338010.1080/00051144.2021.1938477https://doaj.org/article/61755681e4d042e0802e734d9c33d8f02021-10-01T00:00:00Zhttp://dx.doi.org/10.1080/00051144.2021.1938477https://doaj.org/toc/0005-1144https://doaj.org/toc/1848-3380Artificial Bee Colony (ABC) algorithm is a meta-heuristic algorithm, is inspired by the bee’s food search behaviour based on swarm intelligence. Successful applications were performed on many optimization problems using this algorithm rising in popularity over the past few years. The update mechanism of the ABC algorithm, despite the fact that its exploration is good, faces the problem of convergence performance. For solving convergence problem of ABC Algorithm An Artificial Bee Colony Algorithm Based Fitness Weighted Search (ABCFWS) algorithm proposed in this paper. In this approach, an intelligent search space is proposed instead of the random search space of the ABC algorithm. In this method, the fitness values of the food source and the selected neighbour food source are taken as weights and a more balanced search space was found in the direction of the food source with better fitness value. The proposed method has been applied to 28 unconstrained numerical optimization test problems with different characteristics and the results were compared with the ABC algorithm variations. The results show that the proposed method is successful and competitive.Yuksel CelikTaylor & Francis Grouparticleartificial bee colonymeta-heuristic optimizationcontinuous optimizationControl engineering systems. Automatic machinery (General)TJ212-225AutomationT59.5ENAutomatika, Vol 62, Iss 3-4, Pp 300-310 (2021)
institution DOAJ
collection DOAJ
language EN
topic artificial bee colony
meta-heuristic optimization
continuous optimization
Control engineering systems. Automatic machinery (General)
TJ212-225
Automation
T59.5
spellingShingle artificial bee colony
meta-heuristic optimization
continuous optimization
Control engineering systems. Automatic machinery (General)
TJ212-225
Automation
T59.5
Yuksel Celik
An enhanced artificial bee colony algorithm based on fitness weighted search strategy
description Artificial Bee Colony (ABC) algorithm is a meta-heuristic algorithm, is inspired by the bee’s food search behaviour based on swarm intelligence. Successful applications were performed on many optimization problems using this algorithm rising in popularity over the past few years. The update mechanism of the ABC algorithm, despite the fact that its exploration is good, faces the problem of convergence performance. For solving convergence problem of ABC Algorithm An Artificial Bee Colony Algorithm Based Fitness Weighted Search (ABCFWS) algorithm proposed in this paper. In this approach, an intelligent search space is proposed instead of the random search space of the ABC algorithm. In this method, the fitness values of the food source and the selected neighbour food source are taken as weights and a more balanced search space was found in the direction of the food source with better fitness value. The proposed method has been applied to 28 unconstrained numerical optimization test problems with different characteristics and the results were compared with the ABC algorithm variations. The results show that the proposed method is successful and competitive.
format article
author Yuksel Celik
author_facet Yuksel Celik
author_sort Yuksel Celik
title An enhanced artificial bee colony algorithm based on fitness weighted search strategy
title_short An enhanced artificial bee colony algorithm based on fitness weighted search strategy
title_full An enhanced artificial bee colony algorithm based on fitness weighted search strategy
title_fullStr An enhanced artificial bee colony algorithm based on fitness weighted search strategy
title_full_unstemmed An enhanced artificial bee colony algorithm based on fitness weighted search strategy
title_sort enhanced artificial bee colony algorithm based on fitness weighted search strategy
publisher Taylor & Francis Group
publishDate 2021
url https://doaj.org/article/61755681e4d042e0802e734d9c33d8f0
work_keys_str_mv AT yukselcelik anenhancedartificialbeecolonyalgorithmbasedonfitnessweightedsearchstrategy
AT yukselcelik enhancedartificialbeecolonyalgorithmbasedonfitnessweightedsearchstrategy
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