Supplier Selection Process Based on Fuzzy Logic

Abstract

In Kenyan governmental organizations, supplier selection during procurement process is regulated by the Public Procurement and Asset Disposal act. The act requires the selection to be done on technical and financial basis, taking into consideration price, quality, time and service. The common way of selecting suppliers is by forming an evaluation committee which takes considerable time and may be characterized by biases and associated costs. Furthermore, the “quality” and “service” factors advised by the act are imprecise and subjective during an evaluation process and also challenging to quantify. This study presents an approach to help decision-makers evaluate potential suppliers by utilizing fuzzy inference system. Initially, the main quantitative and qualitative criteria used in supplier selection process in the construction service industry were identified from literatures and experts through structured questionnaires. After ranking the identified criteria, a Matlab Fuzzy Inference System (FIS) was utilized to develop the selection model. The proposed model was tested using a real tender for construction works in a government office block. We realized that the proposed model makes the selection process more systematic and achieved a shorter turn-around time as compared to an evaluation committee. It was concluded that using the Fuzzy inference system resulted in an optimum solution and thus can support in decision making when selecting suppliers thus contributes to the advancement of e-procurement in supply chain management.