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Employing Genetic Algorithms to minimise the Bullwhip Effect in an online efficient-responsive supply chain | IEEE Conference Publication | IEEE Xplore

Employing Genetic Algorithms to minimise the Bullwhip Effect in an online efficient-responsive supply chain


Abstract:

The bullwhip effect in supply chains has been observed through a number of previous important works. How to effectively minimise the bullwhip effect, however, remains und...Show More

Abstract:

The bullwhip effect in supply chains has been observed through a number of previous important works. How to effectively minimise the bullwhip effect, however, remains under-investigated, and is still an open research topic. This paper investigates whether genetic algorithms (GAs) can effectively minimise the bullwhip effect in an efficient-responsive supply chain. To achieve this goal, we established a comprehensive model for such a supply chain with orders updated on a weekly basis, and then the GAs were utilised to find the optimal ordering policy, and lead time sets for supply chain participants employing a moving average forecasting technique. An important contribution of this research is that the simulated supply chain is online and efficient-responsive, and hence more realistic than existing models. Experimental results demonstrate that the genetic algorithm is effective in minimising the bullwhip effect.
Date of Conference: 22-24 July 2009
Date Added to IEEE Xplore: 18 August 2009
ISBN Information:
Conference Location: Chicago, IL, USA

References

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