دانلود رایگان مقاله انگلیسی چارچوب تصمیم گیری علمی برای انتخاب تامین کننده تحت فواصل بازه محیط فازی - هینداوی 2017

This paper proposes a new scientific decision framework (SDF) under interval valued intuitionistic fuzzy (IVIF) environment for supplier selection (SS). The framework consists of two phases, where, in the first phase, criteria weights are estimated in a sensible manner using newly proposed IVIF based statistical variance (SV) method and, in the second phase, the suitable supplier is selected using ELECTRE (ELimination and Choice Expressing REality) ranking method under IVIF environment. This method involves three categories of outranking, namely, strong, moderate, and weak. Previous studies on ELECTRE ranking reveal that scholars have only used two categories of outranking, namely, strong and weak, in the formulation of IVIF based ELECTRE, which eventually aggravates fuzziness and vagueness in decision making process due to the potential loss of information. Motivated by this challenge, third outranking category, called moderate, is proposed, which considerably reduces the loss of information by improving checks to the concordance and discordance matrices. Thus, in this paper, IVIF-ELECTRE (IVIFE) method is presented and popular TOPSIS method is integrated with IVIFE for obtaining a linear ranking. Finally, the practicality of the proposed framework is demonstrated using SS example and the strength of proposed SDF is realized by comparing the framework with other similar methods.

8. Conclusion

In this study, we have demonstrated a new computational framework for cloud vendor selection by proposing IVIF, which is an extension to ELECTRE under IVIF environment with three categories of outranking relation for the construction of concordance and discordance matrices. This new scheme also combines TOPSIS ranking method for achieving linear preference order. The proposed IVIFE method represents vagueness better by adopting IVIF concept.The method tackles the issue of information loss better by preserving the interval concept during concordance and discordance estimation. The proposed IVIFE method also handles information loss and vagueness better by constructing concordance and discordance matrices for all three outranking categories under both lower and upper bounds separately. The introduction of the third category (moderate) mitigates the problem of vagueness and information loss within the data by bringing out additional constraint checks for concordance and discordance matrices. This proposal also helps DMs to make rational decisions at uncertain and critical times. An illustrative numerical example is also demonstrated to verify the practicality of the proposed IVIFE scheme.