This paper presents a methodology for the efficient solution of fuzzy optimization problems. Design variables, as well as system parameters are modeled as fuzzy numbers characterized by membership functions. An optimization approach based on approximation concepts is introduced. High quality approximations for system response functions are constructed using the concepts of intermediate response quantities and intermediate variables. These approximations are used to replace the solution of the original problem by a sequence of approximate problems. Optimization techniques for non-differentiable problems which arise in fuzzy optimization are used to solve the approximate optimization problems. Example problems are presented to illustrate the ideas set forth.
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November 1997
Review Articles
Fuzzy Optimization of Complex Systems Using Approximation Concepts
Hector A. Jensen,
Hector A. Jensen
Department of Civil Engineering, Federico Santa Maria University, Casilla 110 V, Valparaiso, Chile
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Abdon E. Sepulveda
Abdon E. Sepulveda
Mechanical and Aerospace Engineering Department, University of California, Los Angeles CA 90095
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Hector A. Jensen
Department of Civil Engineering, Federico Santa Maria University, Casilla 110 V, Valparaiso, Chile
Abdon E. Sepulveda
Mechanical and Aerospace Engineering Department, University of California, Los Angeles CA 90095
Appl. Mech. Rev. Nov 1997, 50(11S): S97-S104
Published Online: November 1, 1997
Article history
Online:
April 20, 2009
Citation
Jensen, H. A., and Sepulveda, A. E. (November 1, 1997). "Fuzzy Optimization of Complex Systems Using Approximation Concepts." ASME. Appl. Mech. Rev. November 1997; 50(11S): S97–S104. https://doi.org/10.1115/1.3101857
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