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基于遗传模拟退火算法的约束求解 被引量:4

Constraint Solving based on Genetic and Simulated Annealing Algorithm
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摘要 简述了遗传算法和模拟退火算法的特点,提出在约束求解中将两者结合起来,能大大提高算法的效率,并对此进行了实例分析。 This paper discusses algorithm and proposes the method for Experiment indicates that the proposed characteristics of the genetic algorithm and the simulated integrating the two algorithms in the process of constraint method is more efficient than other common methods. annealing solving.
作者 孙年芳
出处 《通信技术》 2009年第6期216-218,共3页 Communications Technology
关键词 几何约束求解 参数化设计 遗传模拟退火算法 geometric constraint solving: parametric design genetic simulated annealing algorithm
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参考文献3

  • 1Light R A. Variational Geometry: Modification of Part Geometry by Changing Dimensional Values[C]. in Proceedings of Conference on CAD/CAM Technology in Mechanical Engineering, MIT March, 1982.
  • 2KirkPatriekS. gelattCDandVeeehiMP. OptimizationbySimulated Annealing:Seienee, 1983, 220:671-680.
  • 3Grefenstette JJ. Ineorporating Problem Specific Knowledge into Genetie Algorithms[C]. In:DavisLEd. Genetic Algorithms and Simulated Allnealing, Pitman, 1987, 42-60.

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