Solving geometric constraints with genetic simulated annealing algorithm.
This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.
Liu
Sheng-Li
SL
Department of Computer Science, Zhejiang University, Hangzhou 310027, China. jslsl75@yahoo.com.cn
Tang
Min
M
Dong
Jin-Xiang
JX
D000465:Algorithms; D004738:Engineering; D008957:Models, Genetic; D008962:Models, Theoretical