G. Kelareva and M. Negnevitsky (Australia)
Power systems, maintenance scheduling genetic algorithms.
This paper examines a maintenance scheduling problem in a power system. Due to the large search space, it proved difficult to reach an optimal solution using a traditional genetic algorithm (GA). In order to improve the GA performance, the problem was divided into several layers, each layer representing a part of the initial problem. Each GA layer was used to build sub-schedules, satisfying specified criteria. The sub-schedules were then used as single genes to build up a complete schedule.
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