دانلود مقاله ISI انگلیسی شماره 19364
عنوان فارسی مقاله

انتخاب تامین کننده پایدار: مدل رتبه بندی بر اساس سیستم استنتاج فازی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
19364 2012 10 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Sustainable supplier selection: A ranking model based on fuzzy inference system
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 12, Issue 6, June 2012, Pages 1668–1677

کلمات کلیدی
انتخاب تامین کننده پایدار - مدیریت زنجیره تامین - سیستم استنتاج فازی
پیش نمایش مقاله
پیش نمایش مقاله  انتخاب تامین کننده پایدار: مدل رتبه بندی بر اساس سیستم استنتاج فازی

چکیده انگلیسی

In these days, considering the growth of knowledge about sustainability in enterprise, the sustainable supplier selection would be the central component in the management of a sustainable supply chain. In this paper the sustainable supplier selection criteria and sub-criteria are determined and based on those criteria and sub-criteria a methodology is proposed onto evaluation and ranking of a given set of suppliers. In the evaluation process, decision makers’ opinions on the importance of deciding the criteria and sub-criteria, in addition to their preference of the suppliers’ performance with respect to sub-criteria are considered in linguistic terms. To handle the subjectivity of decision makers’ assessments, fuzzy logic has been applied and a new ranking method on the basis of fuzzy inference system (FIS) is proposed for supplier selection problem. Finally, an illustrative example is utilized to show the feasibility of the proposed method.

مقدمه انگلیسی

Due to the recent agile improvement of network technology and economic globalization, purchasing management has come to play a critical role as a key to business success in supply chain management (SCM). One of the crucial challenges confronted by purchasing managers is the evaluation and selection of the right kind of suppliers compatible to agile systems. Researches carried out in the field of supplier selection have been applying multi-criteria decision making methods, such as analytic hierarchy process (AHP), analytic network process (ANP), data envelopment analysis (DEA), and mathematical programming [1], [2], [3], [4], [5] and [6]. Readers are referred to visit [7] for a detailed account. Nowadays, sustainable development has become a buzzword that received a lot of attentions in many domains such as manufacturing [8], business development [9], tourism [10], and agriculture [11]. Also, in SCM both academics and practitioners consider the sustainable issues in their works. Sustainable SCM is the management of material, information and capital flows, as well as cooperation among companies along the supply chain, while taking into account the goals from all three dimensions, such as economic, environmental and social, of sustainable development derived from customer and stakeholder requirements [12]. To achieve a sustainable supply chain, all of the members in the chain from suppliers to top managers must have affinity with sustainability. Even though many publications exist on supplier selection, the research on sustainable supplier selection [13] and [14] is not adequate. To select the appropriate suppliers, two subjects including importance degree of the selection criteria, and suppliers’ performance with respect to these criteria are essential [15]. These two subjects need to be verified with the relevant decision makers. Decision makers normally prefer to answer the questions in linguistic terms instead of numerical form. Linguistic term is simple and tangible for them to express their perceptions. This might be a way of securing the company's information. But very often, they are obligated to answer the qualitative questions in quantitative form. Therefore, the subjectivity of human assessments is missed. To handle this issue and deal with the vagueness that is being existed in the supplier selection process, application of fuzzy logic is explored in this article. Some researchers have used fuzzy concepts for supplier selection issue [16], [17], [18], [19] and [20]. Also, Ordoobadi proposed a mathematical algorithm by applying fuzzy membership functions to rank the suppliers [15]. However, in case of large number of suppliers and criteria this method is quite time consuming and the final results of ranking are very close to each other. Therefore, the ranking results from this method may not be accurate. So, this paper focused on the said limitations and applies the FIS system to overcome the drawbacks of Ordoobadi's [15] model. Further, Carrera and Mayorga applied the FIS system for supplier selection. But, they did not assign the importance of weights for the selected indicators (criteria and sub-criteria). In their model, the fuzzy rules for each FIS system did not envelop all possible characteristics of suppliers [21]. So, this paper puts importance on weights of criteria and sub-criteria that are allocated in the proposed model considering sustainable issues. From the available literature it may be pointed that sustainable supplier selection issue was not yet considered in FIS system in earlier works. This paper is organized to determine the sustainable supplier selection indicators through the literature survey. Then, a new ranking method for FIS is suggested using those criteria and sub-criteria onto selecting the best suppliers.

نتیجه گیری انگلیسی

This paper introduces a fuzzy ranking model for supplier selection in SCM. The main contributions of this work are summarized as follows: (1) Sustainable supplier selection: to date, there are very few studies considering sustainable issue in the supplier selection problem. The selection indicators on the basis of sustainable aspect are gathered through the literature and these are passed to the model. (2) Very often, the same relative importance of indicators is considered in supplier selection problem. But in practice it needs to be different from one indicator to another. The importance of criteria and sub-criteria weights depends on the decision makers’ preference as proposed in the model. (3) Normally decision makers express their assessments in linguistic term instead of pure numbers. Therefore, the degree of subjectivity is kept in the proposed model. This model paves the way to mitigate the subjectivity in the decision making problems. (4) The proposed model can be executed for any number of suppliers and indicators in large companies. (5) Although many attempts have been made for the supplier selection, considering sustainable issue for this problem remains a challenge. In addition, how to assign orders to the best suppliers in the model can be a subject for future research.

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