Abstract

Chaher ALZAMAN, Amar RAMUDHIN, Akif A. BULGAK

Abstract : This work aims at solving a challenging MIP model for the design of supply chains with nonlinear functions that represent the cost of quality. The model minimizes the cost of quality along with production and transportation costs while deciding which production lines to open or close. To solve the model, a genetic algorithm is used coupled with a gradient search methodology. The overall model is solved and results are presented and discussed. The results pave the way for many future possibilities. Now that the cost or quality is integrated as a cost parameter in a supply chain network model, intelligent decisions could be made to reduce quality non-conformance cost while maintaining moderate operational costs. It can also be used both as an incentive and a way to educate subcontractors on the benefits of operating more efficiently in a collaborative supplier relationship program.

Keywords : nonlinear Programming ; Supply Chain Network Design ; Cost of Quality ; Genetic Algorithm ; Gradient Search Method

Year : 2011
Issue : 3
Volume : 4

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