| Supply Chain Management (SCM) has become an essential component for the success of competitive businesses. SCM is concerned with the planning and controlling of the flow of goods, information, and materials across the whole supply chain from the various suppliers through multiple logistics and productions to distributions and to customers. One of the critical challenges that a purchasing department faces is the evaluation and selection of an appropriate supplier. Supplier evaluation is a decision making process consisting of several conflicting attributes and factors that are both tangible and intangible. By considering these factors, many methods and techniques have been improved and developed based on multiple criteria. These methods and techniques assess and select suppliers by weighting, scoring, voting on relevant sets of criteria, and comparing supplier performance. However, these methods and techniques are still fallible due to human judgment and the lack of capability to deal with the instrumental and conceptual uncertainties that are involved in the supplier evaluation process. In order to choose the most suitable supplier, the methods and technologies have to integrate all relevant criteria. This thesis provides a Fuzzy Inference System (FIS) approach for SCM, especially in supplier evaluation. The FIS is a decision support tool which has ability to solve the multiple criteria problem by using the if-then rules from a knowledge base. Here, the supplier evaluation problem is solved developing a FIS that is implemented with use of the MATLAB Fuzzy Logic Toolbox. |
