Derandomizing Approximation Algorithms Based on Semidefinite Programming

Derandomizing Approximation Algorithms Based on Semidefinite Programming

Remarkable breakthroughs have been made recently in obtaining approximate solutions to some fundamental NP-hard problems, namely Max-Cut, Max k-Cut, Max-Sat, Max-Dicut, Max-bisection, k-vertex coloring, maximum independent set, etc. All these breakthroughs involve polynomial time randomized algorithms based upon semidefinite programming, a technique pioneered by Goemans and Williamson. In this ...

Derandomizing Semidefinite Programming Based Approximation Algorithms

Remarkable breakthroughs have been made recently in obtaining approximate solutions to some fundamental NP Complete problems namely Max Cut Max k Cut Max Sat Max Dicut Max Bisection k Vertex Coloring Independent Set etc These breakthroughs all involve polynomial time randomized algorithms based upon Semide nite Programming a technique pioneered by Goemans and Williamson In this paper we give te...

Semidefinite Programming and Approximation Algorithms: A Survey

Computing approximately optimal solutions is an attractive way to cope with NP-hard optimization problems. In the past decade or so, semidefinite programming or SDP (a form of convex optimization that generalizes linear programming) has emerged as a powerful tool for designing such algorithms, and the last few years have seen a profusion of results (worst-case algorithms, average case algorithm...

Csc5160: Combinatorial Optimization and Approximation Algorithms Topic: Semidefinite Programming 22.1 Semidefinite Programming Problem

In this lecture, we provide another class of relaxations, called Semidefinite Programming Relaxation. These serve as relaxations for several NP-hard problems, in particular, for problems that can be expressed as strict quadratic programs. The relaxed problems, together with techniques like randomized rounding, give good approximation algorithms to hard combinatorial problems. We will illustrate...

On the Optimality of Some Semidefinite Programming-Based Approximation Algorithms under the Unique Games Conjecture