Solving nonlinear multi-objective optimization problems with fuzzy relation inequality constraints regarding Archimedean triangular norm compositions

We propose an approach to solve a nonlinear multi-objective problem subject to fuzzy relation inequalities with max-Archimedean-t-norm composition by a genetic algorithm. The additive generator of Archimedean t-norms is utilized to reform the existent genetic algorithm to solve the constrained nonli...

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Veröffentlicht in:	Fuzzy optimization and decision making Jg. 11; H. 3; S. 299 - 335
Hauptverfasser:	Khorram, E., Ezzati, R., Valizadeh, Z.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2012 Springer Science + Business Media B.V Springer Nature B.V
Schlagworte:	Artificial Intelligence Calculus of Variations and Optimal Control; Optimization Decision making Fuzzy Fuzzy logic Fuzzy set theory Fuzzy sets Generators Genetic algorithms Inequalities Integer programming Linear programming Mathematical Logic and Foundations Mathematical models Mathematical programming Mathematics Mathematics and Statistics Methods Nonlinearity Norms Operations Research/Decision Theory Optimization Pareto optimum Probability Theory and Stochastic Processes Studies Efficient solutions Multi-objective optimization Archimedean t-norm Fuzzy relation inequality Genetic algorithms
ISSN:	1568-4539, 1573-2908
Online-Zugang:	Volltext
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