Economic dispatch by ant colony search algorithm

Sum-Im T.

Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/15137

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DC Field	Value	Language
dc.contributor.author	Sum-Im T.
dc.date.accessioned	2021-04-05T04:32:43Z	-
dc.date.available	2021-04-05T04:32:43Z	-
dc.date.issued	2004
dc.identifier.other	2-s2.0-11244271933
dc.identifier.uri	https://ir.swu.ac.th/jspui/handle/123456789/15137	-
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-11244271933&partnerID=40&md5=0f8e995c916932e24e3d282c95d2cd07
dc.description.abstract	In this paper, ant colony search algorithm (ACSA) is proposed to solve the economic dispatch (ED) with transmission losses problem. ACSA is a new cooperative agents approach, which is inspired by the observation of the behaviors of real ant colonies on the topic of ant trail formation and foraging methods. In the ACSA, a set of cooperating agents called "ants" cooperates to find a good solution for economic dispatch problem. The merits of ACSA are parallel search and optimization capabilities. The feasibility of the proposed method is tested on the IEEE 30 bus system and compared to Lambda iteration method and genetic algorithm.
dc.subject	Dynamic programming
dc.subject	Hydroelectric generators
dc.subject	Iterative methods
dc.subject	Linear programming
dc.subject	Optimization
dc.subject	Problem solving
dc.subject	Quadratic programming
dc.subject	Ant colony search algorithms
dc.subject	Cooperating agents
dc.subject	Economic dispatch
dc.subject	Homogeneous linear programming (HLP)
dc.subject	Algorithms
dc.title	Economic dispatch by ant colony search algorithm
dc.type	Conference Paper
dc.rights.holder	Scopus
dc.identifier.bibliograpycitation	2004 IEEE Conference on Cybernetics and Intelligent Systems. (2004), p.416-421
Appears in Collections:	Scopus 1983-2021

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