دانلود رایگان مقاله انگلیسی انتخاب تامین کننده با استفاده از مدل چند معیاری TOPSIS فازی برای واحد تولید استیل - الزویر 2018

Abstract

Selection of supplier is very critical problem in supply chain management (SCM). In the recent years, selection of suppliers in the supply chain has become very decisive to mould a trade-off between the qualitative and quantitative criteria. These criteria are considered for making final decisions on supplier selection advertently and comprehensively. However, these decisions usually involve in various criteria or objectives to compromise among all possible conflicting parameters. This study deals with the uncertain issue of the supplier selection using integrated TOPSIS model for multi criteria decision making(MCDM). The advantage is that it distinguishes between the cost (less the better) and benefit (more the better) criteria and select the solutions which are closest and farthest from the positive and negative ideal solution. Sensitivity analysis is carried out to investigate the effect of criteria weights on the supplier selection. A computative model is illustrated for a small scale steel manufacturing unit in India.

5. Conclusions

Being one of the most crucial decision making events for organization, supplier selection plays an important role to acquire competitive benefits. To accomplish this goal, the management should apply a successful model and select appropriate criteria for selection of supplier. Linguistic variables play a significant role in decision making process as these determine the performance values which cannot be exhibited into the numerical values. Consequently, with the help of fuzzy set theory DMs’ preferences and experiences are converted into fruitful results by applying linguistic terms to evaluate each criterion with respect to every multiplier. Generally, selection of supplier and evaluation are uncertain and vague. Firstly, it provides the information about various challenges that the firm face while choosing the best supplier in a manufacturing unit for producing the good quality products. Secondly, it identifies the area required for implementation of performances and gives the better understanding for the selection of supplier that comes under the fuzzy conditions. In last step, sensitivity analysis has been performed to investigate the effect of criteria weights on selection of supplier. By relating the closeness coefficient results of the four alternatives as shown in Table 7, it is concluded that S3 is the most preferred supplier and S2 is the least preferred supplier. Furthermore, this proposed model can be used in various MCDM problems such as location selection, project organization, promotion activities and new products development when accessible data are inexact, inaccurate, uncertain and rough by nature.