چارچوب تصمیم فازی چندمعیاری برای انتخاب تامین کننده پایدار با اطلاعات ناقص

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.

Supply chain management (SCM) is a business term that has emerged in the last few decades and has been gaining in popularity ever since. The typical definition of the term supply chain management [1] is as follows: The supply chain comprises all those activities associated with the transformation and flow of goods and services, including their attendant information flows, from the sources of materials to end users. Management refers to integration of all these activities, both internal and external to the firm. Nowadays, consideration is given to the convergence of green/environmental and sustainable SCM. 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 goals from all three dimensions of sustainable development – economic, environmental and social – derived from customer and stakeholder requirements [2]. In doing so, the focus on environmental management and operations is moved from local optimization of environmental factors to consideration of the entire supply chain during the production, consumption, customer service and post-disposal disposition of products [3]. While the first consideration of sustainability can be traced back to practices of many ancient cultures, more recent attention toward sustainability and the environment can be found in the literature [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24] and [25]. In addition to the academic field, also communities, governments, businesses, international agencies, and non-government organizations are increasingly concerned with establishing a means to monitor performance and to assess progress toward sustainable development [26]. Meanwhile, suppliers are of great importance as triggers for sustainable supply chains (SSC). Further thought shows that partnership with environmentally, socially and economically powerful suppliers should enhance the performance of the supply chain. Additionally, there is a need for supplier management for risks and performance, and eventually a need for an effective, sustainable supplier selection and evaluation process. For these reasons, the aim of the paper is to propose an efficient framework for the measurement of supplier sustainability to improve supply chain performance. There exist various techniques in the literature for evaluating and selecting suppliers, such as data envelopment analysis [27], [28], [29] and [30], mathematical programming [19], [31] and [32], fuzzy set theory [33], [34] and [35], analytic hierarchy process (AHP)/fuzzy AHP [11], [36] and [37], and analytic network process (ANP)/fuzzy ANP [38], [39], [40] and [41]. Readers are referred to [42] for detailed information. Sustainable supplier selection requires the evaluation of suppliers’ performance with respect to several metrics. There are complex relationships among these metrics; therefore, the evaluation methodology should capture these relationships effectively. Moreover, it is difficult to obtain precise preferences of decision makers (DMs) because, (1) The decision data of human judgments with preferences are often vague, (2) As improvement of sustainability depends on environmental (planet), social (people) and economical (profit) aspects, DMs may not be able to evaluate suppliers from all these aspects. While one DM might have economic expertise, another might have experience with environment-related issues. A model that can provide a solution even without enough information should be developed to address all the issues discussed above. Incomplete preference relations [43], [44], [45], [46], [47], [48] and [49] can deal with this problem. Since each expert has his/her own experience, he/she could have some difficulties while trying to give his/her preferences in a complete manner. This may be due to an expert not having a precise or sufficient level of knowledge of the problem, or because that expert is unable to judge the degree to which some options are better than others [50]. Also due to time pressure, the DM may develop an incomplete linguistic preference relation in which some of the elements are missing. In such situations, experts are forced to provide incomplete preference relations. These show us that the group decision process needs to derive a single group preference from a number of incomplete individual preferences. Therefore, it is worth paying attention to this issue and this paper focuses on incomplete preference relations while making decisions. While dealing with missing preferences of DMs, the solution procedure should also consider the dependence and interactions among criteria. The increasing complexity and uncertainty of the socio-economic environment makes it less possible to assume all criteria as independent. Hence, this work proposes a new integrated group decision approach based on the ANP [51] method with incomplete linguistic preferences in fuzzy environments [52]. The ANP [53], [54], [55] and [56] approach is applicable to this study since it allows easy discovery of relations inside the complex problem. ANP can overcome the problem of dependence and feedback among criteria or alternatives. Simultaneously, with the help of fuzzy incomplete preferences, this integrated method can deal with uncertainty of DMs and missing data. As incomplete fuzzy preferences are not widespread currently, the main contribution of this paper is the integration of incomplete preferences into ANP and usage of this integration in sustainable supplier selection problem. No study exists in the literature that combines incomplete preference relations with other methods or any applications in the supply chain field. The paper is organized as follows. Section 2 introduces the SSC concept and the evaluation framework for sustainable supplier selection. Section 3 describes the methodology adopted in the paper and characterizes the novel computational procedure. Section 4 includes an implementation of the proposed evaluation framework through the case study and presents the results. Section 5 concludes the paper.

Finding an effective supplier selection model with the goal of sustainability is one of the most important issues before a strategic partnership can be formed. This study proposed a novel fuzzy MCDM framework for an effective sustainable supplier evaluation problem. Considering the increasing complexity and uncertainty of the socio-economic environment, it's less possible to assume all the evaluations in a complex model can be performed with perfect information. Moreover, supplier selection decisions are often made under time pressure, the DMs may have limited expertise related to the problem or have limited attention and information processing capabilities, or some of the decision alternatives may be hard to compare. For this reason, an integrated methodology based on fuzzy ANP and incomplete preference relations is proposed. An empirical case study was used to exemplify the proposed framework. From the analysis of the literature published so far, both at industrial and at scientific research levels, three main conclusions can be drawn: Within the amount of literature available for SSC, scientific working papers, theses and reports have been published only in the form of perfect information. Although many studies on the GDM area exist, authors are probably still not very aware of the potential in completion of missing values. To date, there are very few incomplete preference structured accounts of the applications in the literature, and none focus on the issue of sustainable supplier selection. To our knowledge, no previous work has investigated this subject using this kind of integrated method. As the proposed approach is novel, it might be applied to other GDM problems. We tried to look at the issue of sustainable supplier selection problem with the incomplete preferences, and this approach can be used for such situations in the important GDM problems. To extend the proposed method, incomplete linguistic preferences [50] can be used to estimate the missing values. This may be a subject of future research.