A fixed point iterative approach to integer programming and its distributed computation

Abstract

Integer programming is concerned with the determination of an integer or mixed-integer point in a polytope. It is an NP-hard problem and has many applications in economics and management. Although several popular methods have been developed for integer programming in the literature and extensively utilized in practices, it remains a challenging problem and appeals for more endeavors. By constructing an increasing mapping satisfying certain properties, we develop in this paper an alternative method for integer programming, which is called a fixed point iterative method. Given a polytope, the method, within a finite number of iterations, either yields an integer or mixed-integer point in the polytope or proves no such point exists. As a very appealing feature, the method can easily be implemented in a distributed way. Furthermore, the construction implies that determining the uniqueness of Tarski’s fixed point is an NP-hard problem, and the method can be applied to compute all integer or mixed-integer points in a polytope and directly extended to convex nonlinear integer programming. Preliminary numerical results show that the method seems promising.