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Preventive Maintenance Optimisation Using Evolutionary Hybrid Algorithm

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Abstract

This paper proposes a hybrid algorithm which allows us to optimize maintenance policy by adding the feature of choosing the action's combination suitable to the best maintenance dates. The hybrid approach (called HGACS) combines an ant colony algorithm with a genetic algorithm. This combination is due to the optimized function which has two parts: the first one can be well improved by the ant colony algorithm whereas the second one can not be improved by this method because this sub-function evolves with time. We show that the hybrid algorithm can obtain good results faster than a classical approach especially when the problem depends upon a big number of variables. Hence the developed approach is more suitable for large scale optimization.
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Dates and versions

hal-02358816 , version 1 (12-11-2019)

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Mohamad Samrout, Toufik Benouhiba, Eric Chatelet, Farouk Yalaoui. Preventive Maintenance Optimisation Using Evolutionary Hybrid Algorithm. 2006 International Conference on Service Systems and Service Management, Oct 2006, Troyes, France. pp.620-625, ⟨10.1109/ICSSSM.2006.320533⟩. ⟨hal-02358816⟩
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