Computational Technology Resources - CCP

Paper II.3

A Primitive Crossover for Improving the Reliability of Genetic Algorithms for Structural Optimization

doi:10.4203/ccp.64.2.3

M.H. Imam, M.A. Al-Shihri, "A Primitive Crossover for Improving the Reliability of Genetic Algorithms for Structural Optimization", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 91-97, 2000. doi:10.4203/ccp.64.2.3

Abstract

A new GA operation called "primitive crossover" is introduced for solving the general class of structural optimisation problems. It involves artificially created primitive chromosomes containing only a single non-zero bit. In each generation, the fittest chromosome is selected from the population. Binary addition and subtraction are performed between the selected chromosome and each of the primitive chromosomes before starting the normal GA operations of a simple GA. A set of six test problems of different types including a three-dimensional building frame structure with thirty-two design variables is used to evaluate the algorithm. The results indicate drastically improved reliability as compared to the simple GA.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £52 +P&P)

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 64 COMPUTATIONAL ENGINEERING USING METAPHORS FROM NATURE Edited by: B.H.V. Topping Paper II.3 A Primitive Crossover for Improving the Reliability of Genetic Algorithms for Structural Optimization M.H. Imam and M.A. Al-Shihri Civil Engineering Department, Umm-Al-Qura University, Makkah, Saudi Arabia doi:10.4203/ccp.64.2.3 purchase the full-text of this paper Full Bibliographic Reference for this paper M.H. Imam, M.A. Al-Shihri, "A Primitive Crossover for Improving the Reliability of Genetic Algorithms for Structural Optimization", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 91-97, 2000. doi:10.4203/ccp.64.2.3 Abstract A new GA operation called "primitive crossover" is introduced for solving the general class of structural optimisation problems. It involves artificially created primitive chromosomes containing only a single non-zero bit. In each generation, the fittest chromosome is selected from the population. Binary addition and subtraction are performed between the selected chromosome and each of the primitive chromosomes before starting the normal GA operations of a simple GA. A set of six test problems of different types including a three-dimensional building frame structure with thirty-two design variables is used to evaluate the algorithm. The results indicate drastically improved reliability as compared to the simple GA. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £52 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions