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GECCO
2005
Springer

Ant colony optimization for power plant maintenance scheduling optimization

10 years 5 months ago
Ant colony optimization for power plant maintenance scheduling optimization
In order to maintain a reliable and economic electric power supply, the maintenance of power plants is becoming increasingly important. 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 performance of two different ACO algorithms is compared, including Best Ant System (BAS) and Max-Min Ant System (MMAS), and a detailed sensitivity analysis is conducted on the parameters controlling the searching behavior of ACO algorithms. The results obtained indicate that the performance of the two ACO algorithms investigated 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. In addition, use of the heuri...
Wai-Kuan Foong, Holger R. Maier, Angus R. Simpson
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Wai-Kuan Foong, Holger R. Maier, Angus R. Simpson
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