| Popis: |
This paper deals with a recent approach that tackles the product and the supply chain design issues at the same time and focuses more precisely on the supplier selection problem. The product specificities and the constraints of suppliers are both integrated into product design phase. Usually, the supplier selection problem involves multiple and conflicting objectives. In this work, a multi objective model is formulated to minimize supplying and holding costs of product components and quality rejected items. We study the case of an existent product redesign and we address the problem of supplier selection. Design team proposes several alternatives to improve the product and the aim is to select the best product design with its optimal set of components' suppliers. Thus, a multi-objective programming model for supplier selection is developed. Picking a set of Pareto front for multi-objective optimization problems require robust and efficient methods that can search an entire space. To solve the model, we used a non dominant sorting genetic algorithm (NSGA-II). A numerical experiment is provided at the end to show the applicability of the methodology and to compare it with the simple weighed sum method. |
