A Novel Hybrid Self-Adaptive Bat Algorithm
Nature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date, many variants of this algorithm have emerged for solving continuous as well as combinatorial problems. One of...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/709738 |
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| _version_ | 1832546166332456960 |
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| author | Iztok Fister Simon Fong Janez Brest Iztok Fister |
| author_facet | Iztok Fister Simon Fong Janez Brest Iztok Fister |
| author_sort | Iztok Fister |
| collection | DOAJ |
| description | Nature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date, many variants of this algorithm
have emerged for solving continuous as well as combinatorial problems. One of the more promising variants, a self-adaptive bat algorithm, has recently been proposed that enables a self-adaptation of its control parameters. In this paper, we have hybridized this algorithm using different DE strategies and applied these as a local search heuristics for improving the current best solution directing the swarm of a solution towards the better regions within a search space. The results of exhaustive experiments were promising and have encouraged us to invest more efforts into developing in this direction. |
| format | Article |
| id | doaj-art-dfb5572928854b3c94560e58f5f0867d |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-dfb5572928854b3c94560e58f5f0867d2025-02-03T07:23:49ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/709738709738A Novel Hybrid Self-Adaptive Bat AlgorithmIztok Fister0Simon Fong1Janez Brest2Iztok Fister3Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, SloveniaDepartment of Computer and Information Science, University of Macau, Avenue Padre Tomas Pereira, Taipa, MacauFaculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, SloveniaFaculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, SloveniaNature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date, many variants of this algorithm have emerged for solving continuous as well as combinatorial problems. One of the more promising variants, a self-adaptive bat algorithm, has recently been proposed that enables a self-adaptation of its control parameters. In this paper, we have hybridized this algorithm using different DE strategies and applied these as a local search heuristics for improving the current best solution directing the swarm of a solution towards the better regions within a search space. The results of exhaustive experiments were promising and have encouraged us to invest more efforts into developing in this direction.http://dx.doi.org/10.1155/2014/709738 |
| spellingShingle | Iztok Fister Simon Fong Janez Brest Iztok Fister A Novel Hybrid Self-Adaptive Bat Algorithm The Scientific World Journal |
| title | A Novel Hybrid Self-Adaptive Bat Algorithm |
| title_full | A Novel Hybrid Self-Adaptive Bat Algorithm |
| title_fullStr | A Novel Hybrid Self-Adaptive Bat Algorithm |
| title_full_unstemmed | A Novel Hybrid Self-Adaptive Bat Algorithm |
| title_short | A Novel Hybrid Self-Adaptive Bat Algorithm |
| title_sort | novel hybrid self adaptive bat algorithm |
| url | http://dx.doi.org/10.1155/2014/709738 |
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