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Reducing the negative effects of sales promotions in supply chains using genetic algorithms
Authors:T. O’Donnell  P. Humphreys  R. McIvor  L. Maguire
Affiliation:1. School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin 541004, China;2. School of Mathematical and Statistical Sciences, University of Texas-Rio Grande Valley, Edinburg, TX 78539, USA;3. School of Mathematics Science, Guilin University of Electronic Technology, Guilin 541004, China
Abstract:This paper considers the detrimental effect of promotions on the supply chain (SC), one of the main causes of the bullwhip effect. A genetic algorithm (GA) is proposed to reduce these negative effects. In order to validate the GA, it is used to determine the optimal ordering policy in an online version of the MIT beer distribution game. Subsequently, the GA is applied in a number of experiments involving deterministic and random demand and lead times combined with sales promotions. It is shown how GAs can be used to dampen the impact of the bullwhip effect and can be used to assist supply managers in predicting reorder quantities along the supply chain.
Keywords:Artificial intelligence  Supply chain  Efficiency  Forecasting
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