A Method for Binary Quadratic Programming with Circulant Matrix

Abstract

Binary quadratic programming is a classical combinatorial optimization problem that has many real-world applications. This paper presents a method for solving the quadratic programming problem with circulant matrix by reformulating and relaxing it into a separable optimization problem. The proposed method determines local suboptimal solutions. To solve the relaxing problem, the DCA algorithm it is proposed to calculate the solutions, in the general case, only local suboptimal.