Random search techniques for optimization of nonlinear systems with many parameters

✍ Scribed by George A. Bekey; Sami F. Masri

• Publisher: Elsevier Science
• Year: 1983
• Tongue: English
• Weight: 273 KB
• Volume: 25
• Category: Article
• ISSN: 0378-4754
• DOI: 10.1016/0378-4754(83)90094-0

✦ Synopsis

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, 1.