Reverse logistics management: a decision-making approach under uncertainty, based on Bayesian theory

Abstract

 Once the links of the supply chain within the organizations were integrated, that is to say, it was possible to raise awareness and establish the vision of integrated logistics, it was possible to face the pressure of global competitiveness regarding the handling of equipment, products, components, packaging and even complete technical systems, that had to be recovered, establishing in this way, the management of reverse logistics. Management systems such as PML (product life cycle), ERP (enterprise resource planning), CPM (collaborative processes), CRM (customer relationship), etc. were accepted. However, the greatest challenge in management is the lack of tools for decision making with the information available within these systems. This paper shows an approach to decision making based on the robustness of Bayesian networks under uncertainty for an IDSS (Intelligent Decision Support System).