Abstract
Single- and multicriteria mathematical programming problems with fuzzy constraints are formulated as vector optimization problems. The formulations of such problems, their mathematical models, trade-off schemes, efficiency criteria, and solution methods are considered. Fuzzy logic membership functions are proposed to represent losses due to violations of some boundary conditions. Methods for the normalization of local criteria are given. Algorithms and computational schemes are proposed to solve these problems where the solutions are chosen from a finite set of alternatives. A numerical example is given.
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