Title :
A Genetic Algorithm approach to reducing the Bullwhip Effect by investigating the efficient and responsive strategy in online supply chains
Author :
Lu, J. ; Humphreys, P. ; McIvor, R. ; Maguire, L.
Author_Institution :
Fac. of Bus. & Manage., Univ. of Ulster, Belfast, UK
Abstract :
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.
Keywords :
genetic algorithms; lead time reduction; order processing; supply chain management; Bullwhip effect; genetic algorithm; lead time; online supply chain; optimal ordering policy; responsive strategy; supply chain structure; total mean cost; Business communication; Cost function; Delay; Engineering management; Genetic algorithms; Lead time reduction; Production; Supply chain management; Supply chains; Uncertainty; Bullwhip Effect; Genetic Algorithm (GA); Supply Chain; efficient; responsive;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
DOI :
10.1109/IEEM.2009.5373069
