A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems
Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm a...
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| Published in | Applied soft computing Vol. 11; no. 3; pp. 3021 - 3031 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.04.2011
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1568-4946 1872-9681 |
| DOI | 10.1016/j.asoc.2010.12.001 |
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| Abstract | Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm against those of state-of-the-art algorithms for a set of constrained test problems. For constraint handling, ABC algorithm uses Deb’s rules consisting of three simple heuristic rules and a probabilistic selection scheme for feasible solutions based on their fitness values and infeasible solutions based on their violation values. ABC algorithm is tested on thirteen well-known test problems and the results obtained are compared to those of the state-of-the-art algorithms and discussed. Moreover, a statistical parameter analysis of the modified ABC algorithm is conducted and appropriate values for each control parameter are obtained using analysis of the variance (ANOVA) and analysis of mean (ANOM) statistics. |
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| AbstractList | Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm against those of state-of-the-art algorithms for a set of constrained test problems. For constraint handling, ABC algorithm uses Deb’s rules consisting of three simple heuristic rules and a probabilistic selection scheme for feasible solutions based on their fitness values and infeasible solutions based on their violation values. ABC algorithm is tested on thirteen well-known test problems and the results obtained are compared to those of the state-of-the-art algorithms and discussed. Moreover, a statistical parameter analysis of the modified ABC algorithm is conducted and appropriate values for each control parameter are obtained using analysis of the variance (ANOVA) and analysis of mean (ANOM) statistics. |
| Author | Karaboga, Dervis Akay, Bahriye |
| Author_xml | – sequence: 1 givenname: Dervis surname: Karaboga fullname: Karaboga, Dervis email: karaboga@erciyes.edu.tr – sequence: 2 givenname: Bahriye surname: Akay fullname: Akay, Bahriye email: bahriye@erciyes.edu.tr |
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| Title | A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems |
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