A Fuzzy Logic Approach to Prove Bullwhip Effect in Supply Chains

Abstract

The bullwhip effect in nowadays Supply Chains has become a major source of problems and has attracted supply chain scientists attentions. This paper explores the concept of bullwhip effect in supply chains throughout a completely new approach. Assuming all demands are fuzzy in supply chain, fuzzy If-Then rules are used to show the bullwhip effect. Application of fuzzy logic is due to the fuzzy nature of supply chain problems. The new approach can be the source of inspiration for new solutions to the bullwhip effect in supply chains base on fuzzy logic and fuzzy If-Then rules. Fuzzy time series are widely used in this paper. First for data generation, we apply a modified version of Hwang fuzzy time series with a neural network for defuzzification and finally to show the bullwhip effect, we use Lee fuzzy time series which is based on Fuzzy If-Then rules, Genetic Algorithm and Simulated Annealing

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