توسعه یک سیستم پشتیبانی تصمیم گیری فازی برای خرید کالا با استفاده از فرایند تحلیل شبکه ای فازی

Commodity acquisition is one of the most critical tasks in a firm especially for an accountancy department. Because of imprecise and uncertain product requirements, firm accountants have to make their best effort at this stage. Determining the most critical criteria for commodity acquisition process is a vital means for a firm to balance its limited budget. Therefore, firms have used different methods to cope with this time-consuming and mentally intensive process. This study develops a fuzzy analytic network process model which may help firm accountants in this process. Results derived from a data sample are presented to exemplify the established model. Briefly, this paper proposes an intelligent approach to vendor selection through a fuzzy ANP which takes into consideration quantitative and qualitative elements in evaluating vendor alternatives.

Supply chain management (SCM) has gained influence and became very important for efficient management of industrial activities over the years. The effect of SCM has increased growingly with the developments in areas such as operations research, management and decision-making. If used, SCM provides a competitive advantage to organizations and firms. Commodity acquisition is a part of SCM and does not cover the whole process. Deciding on the correct supplier reduces commodity costs and improves competitiveness in the market. The model presented in this paper helps to structure commodity acquisition by evaluating alternative suppliers through a systemic multi-attribute analytical technique, known as the fuzzy analytic network process (FANP) (Chang, 1996, Kahraman et al., 2006, Mikhailov, 2003a and Mikhailov, 2004). An illustrative example providing additional insights for research and practical application is given in this study. Below, a review of some analytical models for strategy development and decision-making in supply chain management and commodity acquisition is presented.

The FANP methodology is a robust multi-attribute decision-making technique for synthesizing the factors and sub-factors. A fuzzy modification of ANP is proposed in this study for dealing with the commodity acquisition problem. At a time when commodity acquisition activities have an increasing importance for companies, this paper provides insight into the various factors related with the problem. The main contribution of this study is to establish a commodity acquisition model by combining detailed factors and sub-factors in selection of commodity vendors. Opinions of the commodity acquisition experts from various companies over factors and sub-factors have been evaluated in the construction of the model. Implementation of a FANP structure to a real life model is a time consuming process. But the FANP model covers and gives the best solution to the vagueness of the pairwise comparison process considerably. The proposed model provides a user friendly implementation of FANP for a fuzzy decision support system by using Microsoft Excel and Super Decisions. Using these software applications both in the model construction and data processing phase gives a great flexibility for experts and decision makers. An advantage of the study is to be able to adopt the model for a different FANP model in a short time. The proposed methodology also serves as a guideline to the commodity acquisition experts. Although FANP technique used in the proposed model is computationally intensive, the benefits of risk reduction will outweigh the required cost and time. An improved commodity acquisition system implies that company accountants are capable of quickly responding to the variations in the company demands with efficient cost reduction.