A bit-encoded heuristic evolutionary optimization algorithm inspired by the Generalized Extremal Optimization method is presented. The proposed evolutionary approach aims at optimizing a predictive maintenance scheduling problem characterized by an analytically intractable objective function. A preliminary comparison with a standard genetic algorithm on a set of high-dimension cases of the considered maintenance problem shows better performance for the proposed approach.
A generalized extremal optimization-inspired algorithm for predictive maintenance scheduling problems
Maisto Domenico;
2010
Abstract
A bit-encoded heuristic evolutionary optimization algorithm inspired by the Generalized Extremal Optimization method is presented. The proposed evolutionary approach aims at optimizing a predictive maintenance scheduling problem characterized by an analytically intractable objective function. A preliminary comparison with a standard genetic algorithm on a set of high-dimension cases of the considered maintenance problem shows better performance for the proposed approach.File in questo prodotto:
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