Adelaide Research & Scholarship
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| Type: | Conference paper |
| Title: | Ant colony optimization for power plant maintenance scheduling optimization |
| Author: | Foong, W. Maier, H. Simpson, A. |
| Citation: | Proceedings of the 2005 Workshops on Genetic and Evolutionary Computation, Washington, DC, USA, 25-29 June 2005: pp. 354-357 |
| Publisher: | ACM |
| Issue Date: | 2005 |
| Conference Name: | Genetic and Evolutionary Computation Conference (7th : 2005 : Washington, D.C.) |
| Statement of Responsibility: | Wai Kuan Foong, Holger R. Maier & Angus R. Simpson |
| Abstract: | In this paper, a formulation that enables ant colony optimization (ACO) algorithms to be applied to the power plant maintenance scheduling optimization (PPMSO) problem is developed and tested on a 21-unit case study. A heuristic formulation is introduced and its effectiveness in solving the problem is investigated. The results obtained indicate that the performance of ACO algorithms is significantly better than that of a number of other metaheuristics, such as genetic algorithms and simulated annealing, which have been applied to the same case study previously. |
| Keywords: | Ant colony optimization power plant maintenance scheduling heuristics Max-Min Ant System Genetic Algorithm Simulated Annealing |
| Rights: | Copyright 2005 ACM |
| DOI: | 10.1145/1102256.1102335 |
| Published version: | http://dx.doi.org/10.1145/1102256.1102335 |
| Appears in Collections: | Aurora harvest 4 Civil and Environmental Engineering publications |
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