Global optimization for mixed 0-1 programs with convex or separable continuous functions

This paper proposes a global approach for solving mixed 0-1 programming problems containing convex or separable continuous functions. Given a mixed 0-1 polynomial term z=x1x2...xng(Y) where x1,x2,...,xn are 0-1 integer variables and g(Y) is a convex or a separable continuous function, z can be transformed into a set of inequalities where x1,x2,...,xn and g(Y) are separated from each other. Based on this transformation, the original mixed 0-1 program can then be solved by a branch-and-bound method to obtain a global optimum.