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Pareto ant colony optimization based algorithm to solve maintenance and production scheduling problem in parallel machine case

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Abstract

This article presents a new method based on multiobjective Pareto ant colony optimization to resolve the joint production and maintenance scheduling problem. This method is applied to the problem previously developed in for the parallel machines case. This problem was formulated according to a bi-objective approach to find trade-off solutions between both objectives of production and maintenance. Reliability models were used to take into account the maintenance aspect in the model. Two genetic algorithms were compared to approximate the Pareto front. Here, we propose a new algorithm based on Pareto ant colony optimization to improve the solutions quality found in the previous study. The goal is to simultaneously determine the best assignment of production tasks to machines by minimizing the makespan as well as the best periods of preventive maintenance (PM) of the machines by minimizing the unavailability of the production system. The experiments carried out show an improvement of the previous results.
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Dates and versions

hal-02501038 , version 1 (06-03-2020)

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Ali Berrichi, Mohamed Mezghiche, Lionel Amodeo, Farouk Yalaoui. Pareto ant colony optimization based algorithm to solve maintenance and production scheduling problem in parallel machine case. Industrial Engineering (CIE39), Jul 2009, Troyes, France. pp.1210-1215, ⟨10.1109/ICCIE.2009.5223778⟩. ⟨hal-02501038⟩

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