Bullwhip Effect in Multi-Echelon supply Chains
Extended Understanding of the Causes and Control of the Bullwhip Effect in Multi-Echelon Supply Chains
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This book consists of four discrete studies. The first study deals with the development of a multi-echelon simulation model. It is demonstrated that design parameter values that give very poor dynamics across the whole supply chain do not necessarily yield poor dynamics within a single echelon, so it is essential to consider the whole supply chain when setting parameter values. The second study deals with order batching. It is found that the relationship between batch size and demand amplification is non-monotonic. The results show that when the quotient of the average demand and batch size is...
This book consists of four discrete studies. The first study deals with the development of a multi-echelon simulation model. It is demonstrated that design parameter values that give very poor dynamics across the whole supply chain do not necessarily yield poor dynamics within a single echelon, so it is essential to consider the whole supply chain when setting parameter values. The second study deals with order batching. It is found that the relationship between batch size and demand amplification is non-monotonic. The results show that when the quotient of the average demand and batch size is integer, demand amplification does not grow with the increase in batch size. The third study explores the stability boundaries of a multi-echelon capacity constrained supply chain and evolves the policies that minimize the backlog bullwhip effect. The last study deals with the net variance ratio induced by different forecasting techniques with an order-up-to level stock replenishment policy. It is seen that the bullwhip effect and inventory variances have distinct properties depending on the demand forecasting technique.
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