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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 multisolution constraint system. Our experiments have proved the robustness and efficiency
of this method.
Project (No. 6001107) supported by the National Science Foundation of Zhejiang Province 相似文献
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INTRODUCTIONAgeometricconstraintproblemconsistsofasetofgeometricelements,suchaspoints,linesandplanes,andconstraintsonthem ,suchasconstraintsofdistance ,angle ,coincidence,andsoon .Theseelementscanbepositionedwithre specttoeachotherbycomputingasuitableseto… 相似文献
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