Self-Adaptive Artificial Bee Colony for Function Optimization
Artificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concerning its position-updated equation, which is skille...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/4851493 |
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| _version_ | 1832562839254990848 |
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| author | Mingzhu Tang Wen Long Huawei Wu Kang Zhang Yuri A. W. Shardt |
| author_facet | Mingzhu Tang Wen Long Huawei Wu Kang Zhang Yuri A. W. Shardt |
| author_sort | Mingzhu Tang |
| collection | DOAJ |
| description | Artificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concerning its position-updated equation, which is skilled in global search and bad at local search. In order to coordinate the ability of global and local search, we first propose a self-adaptive ABC algorithm (denoted as SABC) in which an improved position-updated equation is used to guide the search of new candidate individuals. In addition, good-point-set approach is introduced to produce the initial population and scout bees. The proposed SABC is tested on 12 well-known problems. The simulation results demonstrate that the proposed SABC algorithm has better search ability with other several ABC variants. |
| format | Article |
| id | doaj-art-c09cf6712736488698c2543c5a0da15e |
| institution | Kabale University |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-c09cf6712736488698c2543c5a0da15e2025-02-03T01:21:43ZengWileyJournal of Control Science and Engineering1687-52491687-52572017-01-01201710.1155/2017/48514934851493Self-Adaptive Artificial Bee Colony for Function OptimizationMingzhu Tang0Wen Long1Huawei Wu2Kang Zhang3Yuri A. W. Shardt4School of Energy and Power Engineering, Changsha University of Science & Engineering, Changsha 410114, ChinaGuizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance & Economics, Guiyang 550004, ChinaHubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Xiangyang 441053, ChinaSchool of Energy and Power Engineering, Changsha University of Science & Engineering, Changsha 410114, ChinaDepartment of Chemical Engineering, University of Waterloo, ON, N2L 3G1, CanadaArtificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concerning its position-updated equation, which is skilled in global search and bad at local search. In order to coordinate the ability of global and local search, we first propose a self-adaptive ABC algorithm (denoted as SABC) in which an improved position-updated equation is used to guide the search of new candidate individuals. In addition, good-point-set approach is introduced to produce the initial population and scout bees. The proposed SABC is tested on 12 well-known problems. The simulation results demonstrate that the proposed SABC algorithm has better search ability with other several ABC variants.http://dx.doi.org/10.1155/2017/4851493 |
| spellingShingle | Mingzhu Tang Wen Long Huawei Wu Kang Zhang Yuri A. W. Shardt Self-Adaptive Artificial Bee Colony for Function Optimization Journal of Control Science and Engineering |
| title | Self-Adaptive Artificial Bee Colony for Function Optimization |
| title_full | Self-Adaptive Artificial Bee Colony for Function Optimization |
| title_fullStr | Self-Adaptive Artificial Bee Colony for Function Optimization |
| title_full_unstemmed | Self-Adaptive Artificial Bee Colony for Function Optimization |
| title_short | Self-Adaptive Artificial Bee Colony for Function Optimization |
| title_sort | self adaptive artificial bee colony for function optimization |
| url | http://dx.doi.org/10.1155/2017/4851493 |
| work_keys_str_mv | AT mingzhutang selfadaptiveartificialbeecolonyforfunctionoptimization AT wenlong selfadaptiveartificialbeecolonyforfunctionoptimization AT huaweiwu selfadaptiveartificialbeecolonyforfunctionoptimization AT kangzhang selfadaptiveartificialbeecolonyforfunctionoptimization AT yuriawshardt selfadaptiveartificialbeecolonyforfunctionoptimization |