title: Solving geometric constraints with genetic simulated annealing algorithm.
abstract: 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.
authors.affiliation: Department of Computer Science, Zhejiang University, Hangzhou 310027, China. jslsl75@yahoo.com.cn
authors.forename: Sheng-Li
authors.initials: SL
authors.lastname: Liu
authors.forename: Min
authors.initials: M
authors.lastname: Tang
authors.forename: Jin-Xiang
authors.initials: JX
authors.lastname: Dong
mesh_terms: D000465:Algorithms; D004738:Engineering; D008957:Models, Genetic; D008962:Models, Theoretical