کاهش اثر شلاق چرمی
Abstract
This paper presents a computational intelligence (CI) approach, which addresses the bullwhip effect in supply chains
(SC). A genetic algorithm (GA) is employed to reduce the bullwhip effect and cost in the MIT beer distribution
game. The GA is used to determine the optimal ordering policy for members of the SC. The paper shows that the
GA can reduce the bullwhip effect when facing deterministic and random customer demand combined with
deterministic and random lead times. The paper then examines the effect of sales promotion on the ordering policies
and shows that the bullwhip effect can be reduced even when sales promotions occur in the SC
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