Supplier pre-selection for platform-based products: a multi-objective approach

Abstract

Selection of appropriate suppliers is an important decision task for enterprises. In literature papers, supplier selection is only considered from the view of components or parts, and evaluation of the overall outsourcing cost and supply risk is not considered from the view of product as a whole. In addition, the traditional process of supplier selection usually happens in the stage of production after the product design has been finished. In fact, suppliers of product components can be pre-selected in the product design stage, which can avoid supplier shortage or high component-bidding cost by modifying the product design scheme. In this research, a new supplier pre-selection method for platform-based products is proposed to obtain the minimal overall outsourcing cost and supply risk probability from the perspective of whole product, help engineers evaluate and improve product design scheme in early time of product design and reduce the probability of design change at the stage of product production. Analytic hierarchy process and reliability matrix are applied to evaluate the supply risk of candidate suppliers and non-dominated sorting genetic algorithm (NSGA-II) is adopted to solve the established optimisation model. A case study is provided to illustrate the effectiveness of the proposed optimisation model and algorithm.