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P. Hajela+ and C-Y. Lin*

+Department of Mechanical Engineering, Aeronautical Engineering and Mechanics, Rensselaer Polytechnic Institute, Troy, NY, United States of America
*Department of Mechanical Engineering, National Taiwan University of Science and Technology,Taipei, Taiwan, Republic of China

Abstract

The paper presents a comparative study between binary-coded (Bga) and real-coded (Rga) genetic algorithms. In a traditional binary-coded genetic algorithm, binary sub-strings corresponding to each design variable are stacked head-to-tail to yield a binary string that represents a particular design. In contrast, the real-coded genetic algorithm does not make use of the binary representation, allowing for gene transformation operations to be conducted on the original real-valued representations of the design variables. The study describes the use of a real-coded genetic algorithm to solve optimization problems containing continuous design variables or a mix of continuous, integer and discrete design variables. An approach for extending real-coded genetic algorithms to problems involving integer and discrete design variables is proposed in this context. Two illustrative problems are solved using both the binary and real-coded genetic algorithm with the focus of exploring relative strengths and weaknesses of these competing methods.

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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.1 Real Versus Binary Coding in Genetic Algorithms: A Comparative Study P. Hajela+ and C-Y. Lin* +Department of Mechanical Engineering, Aeronautical Engineering and Mechanics, Rensselaer Polytechnic Institute, Troy, NY, United States of America *Department of Mechanical Engineering, National Taiwan University of Science and Technology,Taipei, Taiwan, Republic of China doi:10.4203/ccp.64.2.1 purchase the full-text of this paper Full Bibliographic Reference for this paper P. Hajela, C-Y. Lin, "Real Versus Binary Coding in Genetic Algorithms: A Comparative Study", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 77-83, 2000. doi:10.4203/ccp.64.2.1 Abstract The paper presents a comparative study between binary-coded (Bga) and real-coded (Rga) genetic algorithms. In a traditional binary-coded genetic algorithm, binary sub-strings corresponding to each design variable are stacked head-to-tail to yield a binary string that represents a particular design. In contrast, the real-coded genetic algorithm does not make use of the binary representation, allowing for gene transformation operations to be conducted on the original real-valued representations of the design variables. The study describes the use of a real-coded genetic algorithm to solve optimization problems containing continuous design variables or a mix of continuous, integer and discrete design variables. An approach for extending real-coded genetic algorithms to problems involving integer and discrete design variables is proposed in this context. Two illustrative problems are solved using both the binary and real-coded genetic algorithm with the focus of exploring relative strengths and weaknesses of these competing methods. 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)
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