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Group decision making using interval-valued intuitionistic fuzzy soft matrix and confident weight of experts

Das S., Kar S., Pal T.

Journal of Artificial Intelligence and Soft Computing Research

2014

Vol. 4, No. 1

57--77

This article proposes an algorithmic approach for multiple attribute group decision making (MAGDM) problems using interval-valued intuitionistic fuzzy soft matrix (IVIFSM) and confident weight of experts. We propose a novel concept for assigning confident weights to the experts based on cardinals of interval-valued intuitionistic fuzzy soft sets (IVIFSSs). The confident weight is assigned to each of the experts based on their preferred attributes and opinions, which reduces the chances of biasness. Instead of using medical knowledgebase, the proposed algorithm mainly relies on the set of attributes preferred by the group of experts. To make the set of preferred attributes more important, we use combined choice matrix, which is combined with the individual IVIFSM to produce the corresponding product IVIFSM. This article uses IVIFSMs for representing the experts’ opinions. IVIFSM is the matrix representation of IVIFSS and IVIFSS is a natural combination of interval-valued intuitionistic fuzzy set (IVIFS) and soft set. Finally, the performance of the proposed algorithm is validated using a case study from real life.

Application of fuzzy based VIKOR approach for multi-attribute group decision making (MAGDM): a case study in supplier selection

Samantra Ch., Datta S., Mahapatra S. S.

Decision Making in Manufacturing and Services

2012

Vol. 6, no. 1-2

25-39

In today´s competitive global markets, selection of a potential supplier plays an important role to cut production costs as well as material costs of the company. This leads to successful survival and sustainability in a competitive marketplace. Therefore, evaluation and selection of an appropriate supplier has become an important part of supply chain management. The nature of the supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. In order to solve such a kind of MAGDM problems, the development of an effective supplier selection model is evidently desirable. In this paper, an application of the VIKOR method combined with fuzzy logic has been used to solve supplier selection problems with conflicting and non-commensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution. The decision maker wants a solution, which must be closest to the ideal, and the alternatives are evaluated according to all established criteria. Linguistic values are used to assess the ratings and weights for the conflicting factors. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy MAGDM model based on fuzzy sets theory and the VIKOR method has been proposed to deal with the supplier selection problems in the supply chain system. A case study has been illustrated as an application of the proposed model.