Fuzzy Logic Decision Making in Supply Chain Systems; An Approach to Mitigate the Bullwhip Effect

Abstract

The bullwhip effect has been known and existed for many years as an undesirable characteristic in supply chain. This phenomenon negatively impacts the performance of supply chain particularly in keeping stable inventory level. Therefore, any effort to reduce the effect would be beneficial. Enormous number of studies have been focused on the cause and solutions for the bullwhip effect and there has been many of successfully tested experiments to dampen the effect. However, the feasibility of such studies and the actual contributions for supply chain performance are yet up for debate. While the theory and knowledge of the bullwhip effect is well established, there is still lack of holistic engineering framework and method to analyze the problem, diagnose its causes and offer functional remedies. This research work aims to fill this gap by providing a holistic system-based perspective to the bullwhip effect identification and diagnosis and proposing a novel approach to mitigate such effect. The supply chain structure in this study and behavioral features are accomplished by means of system dynamics modeling and fuzzy logic approach. The contribution of the thesis relies not only on the fuzzy logic implementation in system dynamics realm but also improvement in dampening the bullwhip effect with the employed fuzzy logic framework. This research portrays the application of fuzzy set theory in supply chain systems in a case study that exposes the approach, analysis and results to the real-world problem.