โ Scribed by K.P. Dahal; C.J. Aldridge; J.R. McDonald
No coin nor oath required. For personal study only.
In this paper we consider the problem of generator maintenance scheduling (GMS) in power systems. A genetic algorithm with a fuzzy evaluation function is proposed in order to overcome some of the limitations of conventional modelling and solution methods.
A test GMS problem is formulated with a reliability objective and flexible and crisp constraints. A rule base and fuzzy sets are formulated for the objective and the flexible constraint using experience of solutions to the problem, and used to define a fuzzy evaluation function. This is used in a genetic algorithm (GA) with an integer representation of the schedule to solve the test problem.
The results obtained from the GA with the fuzzy evaluation function are compared with those obtained using crisp evaluation functions. The comparison shows that the GA with the fuzzy evaluation function is an effective and practical approach for finding good solutions for GMS with flexible constraints. (~) 1999 Elsevier Science B.V. All rights reserved.
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