Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail
Ant Colony Optimization (ACO) is a meta-heuristic approach for solving hard combinatorial optimization problems. The inspiring source of ACO is the pheromone trail laying and following behavior of real ants which use pheromones as a communication medium. In analogy to the biological example, ACO is...
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2006
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| 在线阅读: | https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf https://ir.uitm.edu.my/id/eprint/85166/ |
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my.uitm.ir.851662024-02-06T12:14:16Z https://ir.uitm.edu.my/id/eprint/85166/ Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail Ismail, Nur Hazima Faezaa Ant Colony Optimization (ACO) is a meta-heuristic approach for solving hard combinatorial optimization problems. The inspiring source of ACO is the pheromone trail laying and following behavior of real ants which use pheromones as a communication medium. In analogy to the biological example, ACO is based on the indirect communication of a colony of simple agents, called (artificial) ants, mediated by (artificial) pheromone trails. The pheromone trails in ACO serve as distributed, numerical information which the ants use to probabilistically construct solutions to the problem being solved and which the ants adapt during the algorithm's execution to reflect their search experience. 2006 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail. (2006) Degree thesis, thesis, Universiti Teknologi MARA (UiTM). |
| institution |
Universiti Teknologi Mara |
| building |
Tun Abdul Razak Library |
| collection |
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| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Mara |
| content_source |
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English |
| description |
Ant Colony Optimization (ACO) is a meta-heuristic approach for solving hard combinatorial optimization problems. The inspiring source of ACO is the pheromone trail laying and following behavior of real ants which use pheromones as a communication medium. In analogy to the biological example, ACO is based on the indirect communication of a colony of simple agents, called (artificial) ants, mediated by (artificial) pheromone trails. The pheromone trails in ACO serve as distributed, numerical information which the ants use to probabilistically construct solutions to the problem being solved and which the ants adapt during the algorithm's execution to reflect their search experience. |
| format |
Thesis |
| author |
Ismail, Nur Hazima Faezaa |
| spellingShingle |
Ismail, Nur Hazima Faezaa Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| author_facet |
Ismail, Nur Hazima Faezaa |
| author_sort |
Ismail, Nur Hazima Faezaa |
| title |
Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| title_short |
Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| title_full |
Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| title_fullStr |
Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| title_full_unstemmed |
Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail |
| title_sort |
solving economic dispatch using ant colony optimization (aco) / nur hazima faezaa ismail |
| publishDate |
2006 |
| url |
https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf https://ir.uitm.edu.my/id/eprint/85166/ |
| _version_ |
1792159398172295168 |
| score |
13.250246 |