Fuzzy Set Based Consensus Schemes for Multicriteria Group Decision making Applied to Strategic Planning

This paper studies three consensus schemes based on fuzzy models for dealing with the input of multiple experts in multicriteria decision making. The consensus schemes are based on different aggregation procedures for constructing a collective decision. In the paper, we propose a methodology that makes use of the three consensus schemes implemented by a coordination mode that creates an efficient manner of exploiting the capabilities of each member of the group in a cooperative work. The applicability and efficiency of the proposed methodology is demonstrated through an application related to strategic planning.     

Cost of doing business index in Latin America

Quality & Quantity - The World Bank's Ease of Doing Business Index (EDBI) has been widely used in analyzes of attracting investments and formulating public policies. Despite its importance...     

Group Decision-Based Construction of Scenarios for Multicriteria Analysis in Conditions of Uncertainty on the Basis of Quantitative and Qualitative Information

This study examines a general scheme of multicriteria decision-making under uncertainty based on quantitative and qualitative information. In its original form, the general scheme uses qualitative information at the final decision stage, only if the quantitative information is unable to generate unique solutions. Considering that many problems require objectives based on qualitative information at all decision stages, the results of Ramalho et al. (2019) can provide such solutions. However, the processing of qualitative information in Ramalho et al. (2019) is based on applying a very simple approach to aggregating individual preferences without analyzing any type of consensus information. Therefore, the present study sets out to show that representative combinations of initial data, states of nature or scenarios can be constructed by using qualitative information directly, based on aggregating individual preferences after achieving the necessary consensus. In particular, a new scheme for consensus construction is proposed. Using this scheme enables negative points inherent in traditional approaches to be avoided and uncertainty levels to be reduced when estimating coefficients of objective functions based on qualitative information. An illustrative example is presented to demonstrate the results that the new proposal can achieve.