Probabilistic Methods for Triangulated Models

The paper describes existing applications of probabilistic methods, namely simulated annealing and genetic algorithms, in solving problems concerning triangulated models. Most of applications are related to global optimization triangulation criteria, improvement of shapes of triangles or tetrahedra and positions of vertices, sometimes in the context of digital images. The paper also sums up typical features, main advantages and disadvantages of simulated annealing and genetic algorithms in this context and sums up the triangulation topics where it is more probable that SA/GA would be a useful tool.