TY - JOUR
T1 - Applying genetic algorithms to dampen the impact of price fluctuations in a supply chain
AU - Lu, J.
AU - Humphreys, P.
AU - McIvor, R.
AU - Maguire, L.
AU - Wiengarten, F.
PY - 2012/10/1
Y1 - 2012/10/1
N2 - Genetic Algorithms (GAs) have been identified as an innovative and useful approach for dampening the Bullwhip Effect along supply chains. This paper extends previous work by developing an improved supply chain model that incorporates additional cost factors such as ordering cost, item cost, distribution cost and production cost. The revised model is then used to examine one element of the Bullwhip Effect, i.e. price fluctuation strategies. A GA is employed to determine the ordering policy for each member in the model that minimises cost. The research illustrates how the GA performs if a sales promotion is introduced. From the experimental results, it is shown that a GA can help determine an improved ordering policy and reduce the total cost across the supply chain.
AB - Genetic Algorithms (GAs) have been identified as an innovative and useful approach for dampening the Bullwhip Effect along supply chains. This paper extends previous work by developing an improved supply chain model that incorporates additional cost factors such as ordering cost, item cost, distribution cost and production cost. The revised model is then used to examine one element of the Bullwhip Effect, i.e. price fluctuation strategies. A GA is employed to determine the ordering policy for each member in the model that minimises cost. The research illustrates how the GA performs if a sales promotion is introduced. From the experimental results, it is shown that a GA can help determine an improved ordering policy and reduce the total cost across the supply chain.
KW - Bullwhip Effect
KW - Genetic Algorithms (GAs)
KW - Supply chain management
UR - http://www.scopus.com/inward/record.url?scp=84867063834&partnerID=8YFLogxK
U2 - 10.1080/00207543.2011.630041
DO - 10.1080/00207543.2011.630041
M3 - Article
AN - SCOPUS:84867063834
SN - 0020-7543
VL - 50
SP - 5396
EP - 5414
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 19
ER -