Özet:

The main purpose of the research is to investigate nonlinear dynamics in bullwhip effect and search chaotic behavior. In the paper, a generalized supply chain model is simulated with safety stock regulations to expose the bullwhip effect. A seasonal demand model which fits Poisson distribution is utilized to generate orders from customers to retailers, continuously to distributors and a single factory. Using largest Lyapunov exponent analysis, orders are reconstructed in phase space and investigated chaotic behavior variations. Although it is assumed that increasing fluctuations of demand cause chaos and unpredictability, it is seen that predictability increases in bullwhip effect. In chaotic research aspect, demands from customers are still more chaotic than orders reach to the factory. Due to data generation, it is still a realization of a supply chain, therefore working on real data is suggested. The paper includes implications for giving ideas of nonlinear dynamics of bullwhip effect. This paper provides a novel approach to supply chains with comparing dynamics of demands and orders to identify which exhibits more chaotic behavior.

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