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Random search techniques for optimization of nonlinear systems with many parameters

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  • Bekey, George A.
  • Masri, Sami F.

Abstract

This paper concerns the application of adaptive random search techniques to large parameter optimization and identification problems. A brief review of the algorithm is presented, followed by a discussion of 3 examples: (1) identification of 25 unknown parameters in a nonlinear 5-degree of freedom mechanical system (2) identification of 17 parameters in a nonlinear model of soil mechanics and (3) determination of optimum values of 24 parameters to obtain a match of two response spectra. The results indicate the robustness and applicability of adaptive random search to a wide variety of nonlinear optimization problems.

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  • Bekey, George A. & Masri, Sami F., 1983. "Random search techniques for optimization of nonlinear systems with many parameters," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 25(3), pages 210-213.
    • Handle: RePEc:eee:matcom:v:25:y:1983:i:3:p:210-213
    DOI: 10.1016/0378-4754(83)90094-0
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    Cited by:

    1. Pronzato, Luc & Walter, Eric & Venot, Alain & Lebruchec, Jean-Francois, 1984. "A general-purpose global optimizer: Implimentation and applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 26(5), pages 412-422.
    2. Walter, E. & Piet-Lahanier, H. & Happel, J., 1986. "Estimation of non-uniquely identifiable parameters via exhaustive modeling and membership set theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 28(6), pages 479-490.

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