Abstract
Our work on the Computational Geometry Challenge 2019 on area-optimal polygonizations is based on two key components: (1) sampling the search space to obtain initial polygonizations and (2) optimizing such a polygonizations. Among other heuristics for obtaining polygonizations for a given set P of input points, we discuss how to combine 2-opt moves with a line sweep to convert an initial random (non-simple) polygon whose vertices are given by P into a polygonization P . The actual optimization relies on a constrained triangulation of the interior and exterior of a polygonization to speed-up local modifications of the polygonization to increase or decrease its area.
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