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Journal of Engineering and Applied Sciences

A Genetic Algorithm Procedure for Optimizing Supply Chain under Quality Measures
Douiri Lamiae, Jabri Abdelouahhab and Abdellah El Barkany

Abstract: In this study, we study a model for computing the Cost of Quality (CoQ) across a single-product three-echelon serial Supply Chain (SC). The proposed model deals with the impact of various parameters such as inspection error rate, fraction defective at suppliers and rework rate on the CoQ function as well as the overall quality level and the effect that these internal variables has on the CoQ categories according to the PAF classification. A Genetic Algorithm (GA) based method was developed to optimize the model for determining the optimal CoQ point that reduces costs for the whole supply chain while maintaining an overall quality level QL. Results obtained from Genetic algorithms method are illustrated with numerical examples to highlight the use of these parameters on SC and provide an aid for decision makers to select reliable suppliers and retailers from among many and manage the cost of quality across the logistic route.

How to cite this article
Douiri Lamiae, Jabri Abdelouahhab and Abdellah El Barkany, 2017. A Genetic Algorithm Procedure for Optimizing Supply Chain under Quality Measures. Journal of Engineering and Applied Sciences, 12: 7214-7222.

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