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Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation

Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation
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Author(s): Pavel Holecek (Palacký University Olomouc, Czech Republic), Jana Talašová (Palacký University Olomouc, Czech Republic)and Ivo Müller (Palacký University Olomouc, Czech Republic)
Copyright: 2012
Pages: 24
Source title: Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
Source Author(s)/Editor(s): Vijay Kumar Mago (Simon Fraser University, Canada)and Nitin Bhatia (DAV College, India)
DOI: 10.4018/978-1-61350-429-1.ch021

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Abstract

This chapter describes a system of fuzzy methods designed to solve a broad range of problems in multiple-criteria evaluation, and also their software implementation, FuzzME. A feature common to all the presented methods is the type of evaluation, well suited to the paradigm of fuzzy set theory. All evaluations take on the form of fuzzy numbers, expressing the extent to which goals of evaluation are fulfilled. The system of fuzzy methods is conceived to allow for different types of interaction among criteria of evaluation. Under no interaction, the fuzzy weighted average, fuzzy OWA operator, or WOWA operator are used to aggregate partial evaluations (depending on the evaluator’s requirements regarding type of evaluation). If interactions appear as redundancy or complementarity, the fuzzified discrete Choquet integral is the appropriate aggregation operator. Under more complex interactions, the aggregation function is defined through an expertly set base of fuzzy rules.

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