Abstract
This paper presents a new bi-objective model to deal with an integrated production planning and reliability-based multi-level preventive maintenance (PM) scheduling problem. The production system includes a set of parallel deteriorating machines. The model aims to find the production lot sizes and the sequence and interval of PM activities over a multi-shift planning horizon. The PM activities are classified as the adjustment and replacement ones, each of which has a specific cost and effect on machines. The model serves to minimise the total cost while maximising customer satisfaction. Also, the most profitable customers are identified by applying a hybrid multi-attribute decision making (MADM) approach (BWM-TOPSIS) in order to fulfil their orders in their desirable time windows. Three efficient meta-heuristic algorithms are developed to solve the proposed model for large-scale problems. Besides, TOPSIS method is employed to select the most desirable solution among the obtained Pareto solutions. Finally, a case study is provided to show the applicability of the proposed approach.
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