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An Improved Genetic Algorithm for the Optimization of Composite Structures

[+] Author Affiliations
Vladimir Gantovnik, Georges Fadel

Clemson University, Clemson, SC

Zafer Gürdal

Delft University of Technology, Delft, The Netherlands

Paper No. DETC2006-99423, pp. 427-436; 10 pages
  • ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 32nd Design Automation Conference, Parts A and B
  • Philadelphia, Pennsylvania, USA, September 10–13, 2006
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4255-X | eISBN: 0-7918-3784-X
  • Copyright © 2006 by ASME


This paper describes a new approach for reducing the number of the fitness and constraint function evaluations required by a genetic algorithm (GA) for optimization problems with mixed continuous and discrete design variables. The proposed modification improves the efficiency of the memory constructed in terms of the continuous variables. The work presents the algorithmic implementation of the proposed memory scheme and demonstrates the efficiency of the proposed multivariate approximation procedure for the weight optimization of a segmented open cross section composite beam subjected to axial tension load. Results are generated to demonstrate the advantages of the proposed improvements to a standard genetic algorithm.

Copyright © 2006 by ASME



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