DFNI-I-02-5 “InterCriteria Analysis – A New Approach to Decision Making”
Our goal is to develop a new approach of decision making support, recently defined by the project team and named by us InterCriteria Analysis. Under this approach, arrays of data obtained by the measurement of many objects against many criteria are processed until correlations are calculated for each pair of criteria in the form of intuitionistic fuzzy pairs of values in the [0;1]-interval. The approach renders account of uncertainty, allows processing of arrays with missing data, and handles both numerical data and linguistic variables with introduced ordering.
The InterCriteria Analysis can be successfully applied to problems, where measuring according to some of the criteria is slower or more expensive, which results in delaying or raising the cost of the overall process of decision making. When solving such problems it is necessary to adopt an approach for reasonable elimination of these criteria, in order to achieve economy and efficiency.
The approach has already demonstrated first evidences of its potential, when applied to economic data, and there have been outlined specific areas of its future application, for which we can obtain appropriate test data. Hence, one of the project objectives is specifying the general framework of the problems addressed by the approach. There will be investigated the connections between the new approach and the multicriteria decision making methods, as well as its relation with the cognitive maps. Another project objective is the development of a software application, implementing the InterCriteria Analysis approach.
Used methods: The approach is based on two mathematical formalisms, which are also original developments of the project team: 1. The algebraic apparatus of index matrices for processing of data arrays of diverse dimensions, and 2. The intuitionistic fuzzy sets as a mathematical tool for treating uncertainty.
Expected results: A new approach will be elaborated in details for solving a class of problems that often occur in science, medicine and industry, and have an important economic and social effect. The approach will be provided with a software application, and approbated with real data from fields of medicine, ecology, agriculture, economics, industry, and artificial intelligence.