Decision-aided Tool for Sustainble Inventory Control
نویسندگان
چکیده
The purchasing policy of spare parts for maintenance and the reverse inventory chain logistics has been attracting researcher’s attention in recent years. In spare parts (SP) inventory control the aim is to maintain the inventory at an optimal level and to minimize the purchasing and the inventory costs. This paper deals with integration of the recycled spare parts in the economic models of inventory systems. In order to contribute to a realistic model of the spare parts inventory control, we proposed an approach based on the Dynamic Bayesian Networks (DBN) formalism. This method allows choosing the best proportion between recycled (RSP) and new spare parts (NSP) so as to minimize the costs by taking into account the uncertainties that can occur in the supply chain inventory system. The proposed model includes real data and is validated running the simulation through BayesiaLab software.
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