Supplier selection is usually involved a multi-criteria evaluation to assist decision-making. This study proposed a simple method for vendor selection. The proposed procedure utilizes the structure of criteria in analytic hierarchy process (AHP) model and employs consistent fuzzy preference relations (CFPR) to construct the decision matrices. The advantage of CFPR is computational simplicity and efficiency. The computation can be done by using an Excel spreadsheet or writing a simple computer program. Also, the CFPR method guarantees the consistency of decision matrices. In this paper, a step-by-step empirical example demonstrates the usage of this proposed method.
Supplier (or vendor) selection is an important issue in supply chain management (SCM) for many enterprises. Basically, there are two aspects in the issue of the supplier selection. One aspect is the criteria for evaluation of suppliers and the other aspect is the procedure or method of supplier selection.
How to evaluate a supplier depends on several different criteria (or factors). The criteria, such as price, quality, delivery, reputation, etc., are frequently selected for comparison and evaluation. These criteria can affect the outcome of the decision-making for vendor selection and they can also affect one another. For the past decades, the philosophy of just-in-time (JIT) and total quality management (TQM) in SCM has been employed in various commercial behaviors. The application of JIT and TQM is proved that it can reduce the cost of inventory and purchasing management. This philosophy may change some of the traditional criteria for supplier selection for different types of business. Besides, different companies may have different organization and cultural backgrounds which may also affect the operation in vendor selection. Therefore, which criteria are suitable and should be used for evaluation of suppliers in SCM for an enterprise is crucial.
On the other aspect, with so many criteria and different suppliers, how to choose a suitable and right supplier is important for many corporations in the today’s competitive business. A suitable supplier may become and develop into a cooperative and long-term partnership in SCM, which can help the growth of a company and can be crucial to the success of the business. And hence, a systematical and effective procedure or method to select the most appropriate supplier is imperative.
In this study authors utilize the structure of criteria in analytic hierarchy process (AHP) (Saaty, 1980, Saaty, 1990a and Saaty, 1990b) model and propose an effective and simple procedure using consistent fuzzy preference relations (CFPR) (Herrera-Viedma, Herrera, Chiclana, & Luque, 2004) to construct the decision matrices for rating suppliers. The rest of the paper is arranged as follows. Firstly, the multi-criteria for supplier selection will be reviewed. Secondly, the recent rating methods on supplier selection will be briefly discussed. The proposed method uses the hierarchy of AHP for criteria and CFPR for rating suppliers. Therefore, thirdly, the popular AHP will be briefly described. Then, the proposed rating method using CFPR is presented. Finally, a numerical example using AHP hierarchy with CFPR process for supplier rating is demonstrated.
In SCM, the supplier selection is important in purchasing management. For most companies, many criteria of supplier selection are almost the same for various businesses. The different parts can be carefully chosen and modified according to the individual company need. Beside, the hierarchy of criteria can be revised according to the purchasing strategy.
This study presents a simple and efficient procedure for rating suppliers. The proposed methodology employs the AHP hierarchy for criteria and utilizes consistent fuzzy preference relations (CFPR) method for supplier selection. Using CFPR method, the number of pairwise comparisons in questionnaire can be reduced from n(n − 1)/2 to (n − 1) for a grouped n-criterion. The rest pairwise comparisons are computed by using CFPR method. The computation of CFPR is simple and efficient. Also, using additive transitivity the CFPR method guarantees the consistency in constructing the decision matrices. This paper demonstrates that the proposed method provides a simple and practical way for ranking alternatives in decision-making problems.
