Authors:
Mariana Vassileva
;
Vassil Vassilev
;
Boris Staykov
and
Danail Dochev
Affiliation:
Institute of Information Technologies, Bulgarian Academy of Sciences, Bulgaria
Keyword(s):
Decision Support Systems, Knowledge-based Systems, Multicriteria Decision Making, Multicriteria Optimization, Interactive Methods, Classification-based Scalarizing Problems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Strategic Decision Support Systems
;
Verification and Validation of Knowledge-Based Systems
Abstract:
The paper describes a generalized multicriteria decision support system, called MKO-2, which is designed to model and solve linear and linear integer multicriteria optimization problems. The system implements the innovative generalized classification-based interactive algorithm for multicriteria optimization with variable scalarizations and parameterizations, which is applicable for different types of multicriteria optimization problems (i.e., linear, nonlinear, mixed variables) as well as for different ways of defining preferences by the decision maker. It can apply different scalarizing problems and strategies in the search for new Pareto optimal solutions. The class of the problems solved, the structure, the functions and the user interface of the MKO-2 system are described in the paper. The graphical user interface of MKO-2 system enables decision makers with different degrees of qualification concerning methods and software tools to operate easily with the system. It can be used
both for education and for solving real-life problems. Because of its nature, MKO-2 system applies specific expert knowledge of the field of multicriteria optimization and knowledge-based (expert) subsystems, explicitly representing specific domain knowledge, as well as specific MO solving knowledge, can be included in it concerning different levels of expertise.
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