On a novel multi-swarm fruit fly optimization algorithm and its application
Swarm intelligence is a research field that models the collective behavior in swarms of insects or animals. Recently, a kind of Drosophila (fruit fly) inspired optimization algorithm, called fruit fly optimization algorithm (FOA), has been developed. This paper presents a variation on original FOA t...
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| Vydáno v: | Applied mathematics and computation Ročník 233; s. 260 - 271 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Inc
01.05.2014
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| Témata: | |
| ISSN: | 0096-3003, 1873-5649 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Swarm intelligence is a research field that models the collective behavior in swarms of insects or animals. Recently, a kind of Drosophila (fruit fly) inspired optimization algorithm, called fruit fly optimization algorithm (FOA), has been developed. This paper presents a variation on original FOA technique, named multi-swarm fruit fly optimization algorithm (MFOA), employing multi-swarm behavior to significantly improve the performance. In the MFOA approach, several sub-swarms moving independently in the search space with the aim of simultaneously exploring global optimal at the same time, and local behavior between sub-swarms are also considered. In addition, several other improvements for original FOA technique is also considered, such as: shrunk exploring radius using osphresis, and a new distance function. Application of the proposed MFOA approach on several benchmark functions and parameter identification of synchronous generator shows an effective improvement in its performance over original FOA technique. |
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| ISSN: | 0096-3003 1873-5649 |
| DOI: | 10.1016/j.amc.2014.02.005 |