An Improved Cockroach Swarm Optimization
Hunger component is introduced to the existing cockroach swarm optimization (CSO) algorithm to improve its searching ability and population diversity. The original CSO was modelled with three components: chase-swarming, dispersion, and ruthless; additional hunger component which is modelled using pa...
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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/10.1155/2014/375358 |
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| author | I. C. Obagbuwa A. O. Adewumi |
| author_facet | I. C. Obagbuwa A. O. Adewumi |
| author_sort | I. C. Obagbuwa |
| collection | DOAJ |
| description | Hunger component is introduced to the existing cockroach swarm optimization (CSO) algorithm to improve its searching ability and population diversity. The original CSO was modelled with three components: chase-swarming, dispersion, and ruthless; additional hunger component which is modelled using partial differential equation (PDE) method is included in this paper. An improved cockroach swarm optimization (ICSO) is proposed in this paper. The performance of the proposed algorithm is tested on well known benchmarks and compared with the existing CSO, modified cockroach swarm optimization (MCSO), roach infestation optimization RIO, and hungry roach infestation optimization (HRIO). The comparison results show clearly that the proposed algorithm outperforms the existing algorithms. |
| format | Article |
| id | doaj-art-f57825b2bca04aca94a9d6e7ffaf862f |
| 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-f57825b2bca04aca94a9d6e7ffaf862f2025-02-03T06:06:58ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/375358375358An Improved Cockroach Swarm OptimizationI. C. Obagbuwa0A. O. Adewumi1School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville, Durban 4000, South AfricaSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville, Durban 4000, South AfricaHunger component is introduced to the existing cockroach swarm optimization (CSO) algorithm to improve its searching ability and population diversity. The original CSO was modelled with three components: chase-swarming, dispersion, and ruthless; additional hunger component which is modelled using partial differential equation (PDE) method is included in this paper. An improved cockroach swarm optimization (ICSO) is proposed in this paper. The performance of the proposed algorithm is tested on well known benchmarks and compared with the existing CSO, modified cockroach swarm optimization (MCSO), roach infestation optimization RIO, and hungry roach infestation optimization (HRIO). The comparison results show clearly that the proposed algorithm outperforms the existing algorithms.http://dx.doi.org/10.1155/2014/375358 |
| spellingShingle | I. C. Obagbuwa A. O. Adewumi An Improved Cockroach Swarm Optimization The Scientific World Journal |
| title | An Improved Cockroach Swarm Optimization |
| title_full | An Improved Cockroach Swarm Optimization |
| title_fullStr | An Improved Cockroach Swarm Optimization |
| title_full_unstemmed | An Improved Cockroach Swarm Optimization |
| title_short | An Improved Cockroach Swarm Optimization |
| title_sort | improved cockroach swarm optimization |
| url | http://dx.doi.org/10.1155/2014/375358 |
| work_keys_str_mv | AT icobagbuwa animprovedcockroachswarmoptimization AT aoadewumi animprovedcockroachswarmoptimization AT icobagbuwa improvedcockroachswarmoptimization AT aoadewumi improvedcockroachswarmoptimization |