Abstract
The constraint problem can be transformed to an optimization problem. In this paper a new hybrid algorithm—MSCGA was introduced which mixes genetic algorithm with chaos optimization method. The character of this new method is that the mechanism of the GA was not changed but the search space and the coefficient of adjustment was reduced continually and this can lead generation to evolve to the next generation in order to produce better optimization individuals. It can improve the performance of the GA and get over the disadvantage of the GA. The examination indicates that this algorithm can show a better performance than the normal GA and other hybrid methods in solving a geometric constraint and acquires a satisfying result.
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References
Yuan, B.: Research and Implementation of Geometric Constraint Solving Technology, doctor dissertation of Tsinghua University, pp. 1–8 (1999)
Deming, L.: A hybrid genetic algorithm using chaos for globally optimal solution. System Engineering and Electronics 21(12), 81–84 (1999)
Li, D.: An improved hybrid genetic algorithm. Information and Control 26(6), 449–454 (1997)
Wang, M., Liu, J., Sun, Y.: The hybrid genetic algorithm based on the mutative scale chaos optimization. Control and Decision 17(6), 958–960 (2002)
Liu, S., Tang, M., Dong, J.: Two Spatial Constraint Solving Algorithms. Journal of Computer- Aided Design & Computer Graphics 15(8), 1011–1029 (2003)
Tong, Z., Wang, H., Wang, Z.: Mutative scale chaos optimization algorithm and its application. Control and Decision 14(3), 285–288 (1999)
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© 2004 Springer-Verlag Berlin Heidelberg
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Chunhong, C., Wenhui, L. (2004). The Geometric Constraint Solving Based on Mutative Scale Chaos Genetic Algorithm. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_51
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DOI: https://doi.org/10.1007/978-3-540-30497-5_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24127-0
Online ISBN: 978-3-540-30497-5
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