A computational support for the group consensus reaching process in the fuzzy environment

In this paper we present an intelligent consensus reaching support system within the group of individuals under fuzzy preferences and fuzzy majority. Our solution is based on the idea of soft degree of consensus proposed by Fedrizzi, Kacprzyk, Nurmi and Zadrozny, which is meant as the statement: “most of the individuals agree with the most of the options”. Our new comprehensive model provides an effective support for the discussion guidance in the form of quantitative indices, i.e. sensitivity of individuals, option consensus degree and the cost of preference's changes. This additional measures support and simplify consensus reaching process and improve the degree of total agreement among decision makers.