A Decentralized Production and Distribution Planning Model in an Uncertain Environment

Abstract

Distributed Decision Making (DDM) is a discipline of decision theory in which decision making power is distributed among several decision making units. Supply Chain planning problems usually involve multiple decision makers, making DDM highly suitable for realistic modelling. Furthermore, due to the complexity and dynamism of supply chain environments, accounting for uncertainty is important when modelling a supply chain planning problem. This chapter contributes to existing knowledge on the one hand with a brief literature review of DDM systems developed in the recent past. On the other hand, it contributes a proposed DDM coordination mechanism for a supply chain planning problem with two distributed decision makers, in a multi-echelon context, with multiple product levels. The DDM system’s performance is evaluated under demand uncertainty by applying a fuzzy approach. Computational results show that the proposed distributed model closely approximated the optimal solutions generated by the centralised model, strengthening the evidence for DDM’s applicability to real problems. Finally, the fuzzy approach is shown to be a useful tool for decision makers in evaluating risk in their supply chain planning decisions.