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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Bibliographic Details
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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Summary: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.