SHORTEST PATHS HELP SOLVE GEOMETRIC OPTIMIZATION PROBLEMS IN PLANAR REGIONS

The goal of this paper is to show that the concept of the shortest path inside a polygonal region contributes to the design of efficient algorithms for certain geometric optimization problems involving simple polygons: computing optimum separators, maximum area or perimeter-inscribed triangles, a minimum area circumscribed concave quadrilateral, or a maximum area contained triangle. The structure for the algorithms presented is as follows: (a) decompose the initial problem into a low-degree polynomial number of optimization problems; (b) solve each individual subproblem in constant time using standard methods of calculus, basic methods of numerical analysis, or linear programming. These same optimization techniques can be applied to splinegons (curved polygons). First a decomposition technique for curved polygons is developed; this technique is substituted for triangulation in creating equally efficient curved versions of the algorithms for the shortest-path tree, ray-shooting, and two-point shortest path problems. The maximum area or perimeter inscribed triangle problem, the minimum area circumscribed concave quadrilateral problem and maximum area contained triangle problem have applications to robotics and stock-cutting. The results of this paper appear in E. A. Melissaratos's Ph.D. thesis [Mesh Generation and Geometric Optimization, Rutgers University, New Brunswick, NJ, 1991].