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
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id	my-uitm-ir.85166
record_format	uketd_dc
spelling	my-uitm-ir.851662024-02-06T12:14:16Z Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail 2006 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 https://ir.uitm.edu.my/id/eprint/85166/ https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Musirin, Ismail
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Musirin, Ismail
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
qualification_level	Bachelor degree
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
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2006
url	https://ir.uitm.edu.my/id/eprint/85166/2/85166.pdf
_version_	1794192076243468288

Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail

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