We present a unified framework for designing polynomial time approx- imation schemes (PTASs) for "dense" instances of many NP-hard optimization problems, including maximum cut, graph bisection, graph separation, minimum k-way cut with and without specified terminals, and maximum 3-satisfiability. By dense graphs we mean graphs with minimum degree Ω(n ), although our algorithms solve most of these problems so long as the average degree is Ω(n ). Denseness for non- graph problems is defined similarly. The unified framework begins with the idea of exhaustive sampling: picking a small random set of vertices, guessing where they go on the optimum solution, and then using their placement to determine the placement of everything else. The approach then develops into a PTAS for approximating certain smooth integer programs, where the objective function and the constraints are "dense" polynomials of constant degree.
展开▼
