Reducing the bullwhip effect in supply chains using genetic algorithm and control engineering

Supply chains suffer from bullwhip effect which is the amplified variance of the demand information at the order end of the chain. Differently from the majority of research efforts in reducing the bullwhip efforts that consider business modeling approaches and use information technology enhancements, this paper introduces alternative techniques that mainly focus on using the strength of Genetic Algorithm (GA), PI and PID controllers as tools for the bullwhip reduction. The results show the ability of the proposed techniques in providing substantial reduction specially when compared with the current conventional approaches.