Implementation of a Convexification Technique for Signomial Functions

In this paper, an implementation of a global optimization framework for Mixed Integer Nonlinear Programming (MINLP) problems containing signomial functions is described. In the implementation, the global optimal solution to a MINLP problem is found by solving a sequence of convex relaxed subproblems overestimating the original problem. The described solver utilizes the General Algebraic Modeling System (GAMS) to solve the subproblems, which in each iteration are made tighter until the global optimal solution is found.