Supplier performance management: study of multicriteria techniques and artificial intelligence for group decision

Abstract

Managing suppliers in supply chains includes decision processes in which decisions should be taken by multiple decision makers who judge about criteria, suppliers, strategies, among other actions. Disagreement in judgments by the decision makers can lead to inconsistencies of the decision process and therefore needs to be dealt with. Group decision is a well stablished research stream operations research as well as in artificial intelligence. Although multicriteria techniques are well explored by countless studies, group decision techniques are much less applied to supplier selection and management. Therefore, the objective of this research project is the proposition of decision processes applied to supplier management and based on multicriteria and artificial intelligence techniques for group decision, criteria weight elicitation and classification. This main objective is deployed in several research targets, as detailed in section 1.3. This research project is related to the research project INCT - INSID - National Institute of Decision and Information System, specifically with the research line on "decision models applied to service systems". The focus of application of the proposed models will be the automotive and consumer goods industries due their characteristics. The research project development comprises conceptual and computational modelling and field research. It is aimed to contribute to increase research integrating operations management and decision support techniques; in the long run, it aims to contribute to improve the practices in the companies. (AU)