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A Geometric Constraint Solver Using Chaos Genetic Algorithm

GAO Cheng1, LI Wen-hui2, CAO Chun-hong2   

  1. 1. College of Computer Science and Technology, Beihua University, Jilin 132021, Jilin Province, China;2. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2005-01-03 Revised:1900-01-01 Online:2005-07-26
  • Contact: LI Wen-hui

Abstract: A new hybrid algorithm--mutative scale chaos genet ic algorithm (MSCGA) is presented which mixes genetic algorithm with chaos optim ization method. The character of this new method is that the mechanism of the GA is not changed but the search space and the coefficient of the adjustment of th e optimization parameter are reduced continually, which leads to generation evolution to the next generation in order to produce better optimization indivi duals so as to improve the performance of the GA and get over the disadvantage o f the GA. The examination indicates that this algorithm shows a better performan ce than the normal GA and other hybrid methods in geometric constraint solution and acquires satisfied result.

Key words: geometric constraint solving, chaos optimization metho d, mutative scale chaos genetic algorithm

CLC Number: 

  • TP391