Computational Technology Resources - CCP

O. Hasancebi, F. Erbatur, "Evaluation of Crossover Techniques in Genetic Algorithm based Optimum Structural Design", in B.H.V. Topping, (Editor), "Advances in Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, pp 111-123, 1998. doi:10.4203/ccp.53.3.4

Abstract

Crossover is one of the three basic operators in any genetic algorithm (GA). Several crossover techniques have been proposed and their relative merits are currently under investigation. This paper starts with a brief discussion of the working scheme of genetic algorithms (GAS) and crossover techniques commonly used in previous GA applications. Next, these techniques are tested on two truss size optimization problems, and are evaluated with respect to exploration and exploitation aspects of the search process. Finally, the paper proposes two newly developed crossover techniques, through which a better efficiency of GAS can be obtained. Comparative studies are carried out between the proposed and common crossover techniques, and the results are fully discussed.

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 £75 +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: 53 ADVANCES IN ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping Paper III.4 Evaluation of Crossover Techniques in Genetic Algorithm based Optimum Structural Design O. Hasancebi and F. Erbatur Department of Civil Engineering, Middle East Technical University, Ankara, Turkey doi:10.4203/ccp.53.3.4 purchase the full-text of this paper Full Bibliographic Reference for this paper O. Hasancebi, F. Erbatur, "Evaluation of Crossover Techniques in Genetic Algorithm based Optimum Structural Design", in B.H.V. Topping, (Editor), "Advances in Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, pp 111-123, 1998. doi:10.4203/ccp.53.3.4 Abstract Crossover is one of the three basic operators in any genetic algorithm (GA). Several crossover techniques have been proposed and their relative merits are currently under investigation. This paper starts with a brief discussion of the working scheme of genetic algorithms (GAS) and crossover techniques commonly used in previous GA applications. Next, these techniques are tested on two truss size optimization problems, and are evaluated with respect to exploration and exploitation aspects of the search process. Finally, the paper proposes two newly developed crossover techniques, through which a better efficiency of GAS can be obtained. Comparative studies are carried out between the proposed and common crossover techniques, and the results are fully discussed. 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 £75 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions