Abstract
The geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially; thus the constraint problem can be transformed to an optimization problem. Inspired by the thought of netting fish in our daily life, Wang-Yu Algorithm starts from the most basic characteristics of the random exploring optimization and ties up two special kinds of data-nets firstly in computer by using the tactics of random moving together; then Wang-Yu Algorithm realizes the object of random exploring optimization from a new direction by netting orderly in the all range of exploring and promptly observing the situation after netting. The experiment shows that it can improve the geometric constraint solving efficiency and possess better convergence property than the compared algorithms.
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