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To handle the original optimization problem, fuzzy goal programming is adopted and heuristic algorithms are designed.
To address this problem, fuzzy logic may be an alternative, providing rule-based modeling in which the phenotypic expression of the system is under control (i.e., tension), rather than its individual components.
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In context of such hierarchical problems, Fuzzy goal programming (FGP) approach seems to be more appropriate than other methodologies.
As a tool for modeling nondeterministic problems, fuzzy measures and a fuzzy integral introduced by Sugeno in [1] have been successfully applied to various fields.
Since the subjectivity, imprecision and vagueness in the estimates of a performance rating enter into multiple attribute decision-making (MADM) problems, fuzzy set theory provides a mathematical framework for modelling vagueness and imprecision.
In order to solve this problem, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed.
In this paper, the vehicle routing problem with fuzzy demands (VRPFD) is considered, and a fuzzy chance constrained program model is designed, based on fuzzy credibility theory.
However, the main problem of fuzzy logic is the lack of kinematic approach for fuzzy controller.
The problem of fuzzy robust L2−L∞ filtering for a class of delayed Takagi Sugeno fuzzy systems is investigated in the paper.
To model this problem, a fuzzy chance constrained programming model of that is designed based upon the fuzzy credibility theory.
This paper investigates the problem of fuzzy unknown input observer (FUIO -based FUIO -basedation faultiscrestimationakagi–Sugeno forzy systems.
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