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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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Main Author: Ismail, Nur Hazima Faezaa
Format: Thesis
Language:English
Published: 2006
Online Access:https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf
https://ir.uitm.edu.my/id/eprint/85166/
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spelling 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 Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language 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 13.211869

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