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This research presents an extension to the genetic algorithm approach to reducing the Bullwhip effect by investigating the individual efficient or responsive strategy for each member in different online supply chains. Four types of supply chain structure by positioning the decoupling point will be investigated to determine if the genetic algorithm (GA) can help find optimal ordering policy and lead...
The increase in demand variability as information flows from customers to manufacturers in a supply chain is known as the Bullwhip Effect (BE). Modeling this phenomenon is key in measuring its intensity, aiming at reducing its negative impact on both service and inventory levels in supply chains. This paper proposes a new, more precise mathematical model for quantifying the BE in systems with stochastic...
An important contributory factor to the bullwhip effect is the non-lead-time in the supply chain. This paper investigates the influences of production/distribution lead-time on the bullwhip effect under order-up-to (OUT) policy using control engineering method, comparing the performances of order rate and inventory level in different lead-time situations. When the lead-time is longer, the order rate...
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