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H. Liang and J.Z. Cui

Institute of Computational Mathematics and Science/Engineering Computing, Chinese Academy of Science, Beijing, P.R. China

doi:10.4203/ccp.64.2.4

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H. Liang, J.Z. Cui, "Application of Conception of Distance for the Genetic Algorithm", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 99-103, 2000. doi:10.4203/ccp.64.2.4

Abstract

General Genetic Algorithm(GA) has a deadly weakness which is called premature phenomenon that can result to be convergent to local optimization. The weakness generally is caused by the poor diversity of the population. The paper deeply analyses the shortcoming of GA and introduces the concept of distance to GA in order to increase the diversity of the population. The paper firstly uses distance to define conception radius and diameter on the information of the current generation, and use the radius and diameter to define the parameters of general Genetic Algorithm(GA) which are always constant during the process of computing. To apply the algorithm to resolve many engineering problems, results show it can greatly avoid the premature phenomenon and has more fast convergence speed than other general GA.

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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.4 Application of Conception of Distance for the Genetic Algorithm H. Liang and J.Z. Cui Institute of Computational Mathematics and Science/Engineering Computing, Chinese Academy of Science, Beijing, P.R. China doi:10.4203/ccp.64.2.4 purchase the full-text of this paper Full Bibliographic Reference for this paper H. Liang, J.Z. Cui, "Application of Conception of Distance for the Genetic Algorithm", in B.H.V. Topping, (Editor), "Computational Engineering using Metaphors from Nature", Civil-Comp Press, Edinburgh, UK, pp 99-103, 2000. doi:10.4203/ccp.64.2.4 Abstract General Genetic Algorithm(GA) has a deadly weakness which is called premature phenomenon that can result to be convergent to local optimization. The weakness generally is caused by the poor diversity of the population. The paper deeply analyses the shortcoming of GA and introduces the concept of distance to GA in order to increase the diversity of the population. The paper firstly uses distance to define conception radius and diameter on the information of the current generation, and use the radius and diameter to define the parameters of general Genetic Algorithm(GA) which are always constant during the process of computing. To apply the algorithm to resolve many engineering problems, results show it can greatly avoid the premature phenomenon and has more fast convergence speed than other general 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)
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