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A Genetic Algorithm Approach To Reducing The Bullwhip Effect By Investigating The Efficient And Responsive Strategy In Online Supply Chains

J. Lu, P. Humphreys, R. McIvor, L. Maguire
Published 2009 · Computer Science

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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 time for each member and, at the same time, reduce the impact of the Bullwhip Effect and total mean cost across the online supply chain. It is shown that the optimal supply chain structure that presents better performance on both the total lead time and the mean cost should be employed.
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