Potential reduction algorithms for structured combinatorial optimization problems

Recently Karmarkar proposed a potential reduction algorithm for binary feasibility problems. In this paper, a modified potential function that has more attractive properties is introduced. Furthermore, as the main result, for a specific class of binary feasibility problems a concise reformulation as nonconvex quadratic optimization problems is developed. We introduce a potential function to optimize the new model and report on computational experience with the graph coloring problem, comparing the performance of the three potential functions.