Particle swarm optimization with area extension (AEPSO)
Particle Swarm Optimization (PSO) is one of the evolutionary algorithms which proved to be useful in solving multi-robots tasks. PSO outperforms other evolutionary algorithms, such as GA, in this area. In this paper we introduce a new modified version of PSO called Area Extension PSO (AEPSO). Inform...
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| Format: | Book Section |
| Language: | English |
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IEEE Xplore
2007
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| Online Access: | http://shdl.mmu.edu.my/3178/ http://shdl.mmu.edu.my/3178/1/Particle%20swarm%20optimization%20with%20area%20extension%20%28AEPSO%29.pdf |
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| author | Atyabi, A Phon-Amnuaisuk, S. |
| author_facet | Atyabi, A Phon-Amnuaisuk, S. |
| author_sort | Atyabi, A |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | Particle Swarm Optimization (PSO) is one of the evolutionary algorithms which proved to be useful in solving multi-robots tasks. PSO outperforms other evolutionary algorithms, such as GA, in this area. In this paper we introduce a new modified version of PSO called Area Extension PSO (AEPSO). Information about the environment in extended area together with various heuristics improves the performance of each robot and the group. We believe this AEPSO is suitable to solve problems in environments with large area which have more similarity to real world robotic problems. The result of this study shows a magnificent improvement and the potential of AEPSO, especially in dynamic environments. |
| first_indexed | 2025-11-14T18:09:43Z |
| format | Book Section |
| id | mmu-3178 |
| institution | Multimedia University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:09:43Z |
| publishDate | 2007 |
| publisher | IEEE Xplore |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-31782013-11-20T07:59:01Z http://shdl.mmu.edu.my/3178/ Particle swarm optimization with area extension (AEPSO) Atyabi, A Phon-Amnuaisuk, S. T Technology (General) QA75.5-76.95 Electronic computers. Computer science Particle Swarm Optimization (PSO) is one of the evolutionary algorithms which proved to be useful in solving multi-robots tasks. PSO outperforms other evolutionary algorithms, such as GA, in this area. In this paper we introduce a new modified version of PSO called Area Extension PSO (AEPSO). Information about the environment in extended area together with various heuristics improves the performance of each robot and the group. We believe this AEPSO is suitable to solve problems in environments with large area which have more similarity to real world robotic problems. The result of this study shows a magnificent improvement and the potential of AEPSO, especially in dynamic environments. IEEE Xplore 2007-09 Book Section NonPeerReviewed text en http://shdl.mmu.edu.my/3178/1/Particle%20swarm%20optimization%20with%20area%20extension%20%28AEPSO%29.pdf Atyabi, A and Phon-Amnuaisuk, S. (2007) Particle swarm optimization with area extension (AEPSO). In: IEEE Congress on Evolutionary Computation, 2007. CEC 2007. IEEE Xplore, pp. 1970-1976. ISBN 978-1-4244-1339-3 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4424715 10.1109/CEC.2007.4424715 10.1109/CEC.2007.4424715 10.1109/CEC.2007.4424715 |
| spellingShingle | T Technology (General) QA75.5-76.95 Electronic computers. Computer science Atyabi, A Phon-Amnuaisuk, S. Particle swarm optimization with area extension (AEPSO) |
| title | Particle swarm optimization with area extension (AEPSO) |
| title_full | Particle swarm optimization with area extension (AEPSO) |
| title_fullStr | Particle swarm optimization with area extension (AEPSO) |
| title_full_unstemmed | Particle swarm optimization with area extension (AEPSO) |
| title_short | Particle swarm optimization with area extension (AEPSO) |
| title_sort | particle swarm optimization with area extension (aepso) |
| topic | T Technology (General) QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/3178/ http://shdl.mmu.edu.my/3178/ http://shdl.mmu.edu.my/3178/ http://shdl.mmu.edu.my/3178/1/Particle%20swarm%20optimization%20with%20area%20extension%20%28AEPSO%29.pdf |