Please use this identifier to cite or link to this item: https://doi.org/10.1109/PMAPS.2010.5529004
Title: Generator maintenance scheduling with hybrid evolutionary algorithm
Authors: Srinivasan, D. 
Aik, K.C.
Malik, I.M.
Keywords: Artificial intelligence
Evolution strategy
Fuzzy systems
Genetic algorithm
Hybrid intelligent systems
Maintenance schedule
Particle swarm optimization
Issue Date: 2010
Source: Srinivasan, D.,Aik, K.C.,Malik, I.M. (2010). Generator maintenance scheduling with hybrid evolutionary algorithm. 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010 : 632-637. ScholarBank@NUS Repository. https://doi.org/10.1109/PMAPS.2010.5529004
Abstract: This paper proposes a hybrid evolutionary algorithm to solve the maintenance-scheduling problem for thermal generating units. The proposed approach uses a hybrid Fuzzy-Genetic Algorithm that implements Fuzzy Knowledge Based System to emulate the power plant personnel's experience, and uncertainties in the constraints, while a Genetic Algorithm optimizes the total generating cost and the maintenance cost as the objective functions. Two other effective and practical methods based on Evolution Strategy and Particle Swarm Optimization were also applied for the same problem. Simulations were carried out on a practical thermal power plant consisting of 19 generating units, over a six-month planning horizon. ©2010 IEEE.
Source Title: 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/70422
ISBN: 9781424457236
DOI: 10.1109/PMAPS.2010.5529004
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