Relative Entropy Relaxations for Signomial Optimization

Some transformation techniques with applications in global optimization

In this paper some transformation techniques, based on power transformations, are discussed. The techniques can be applied to solve optimization problems including signomial functions to global optimality. Signomial terms can always be convexified and underestimated using power transformations on the individual variables in the terms. However, often not all variables need to be transformed. A m...

A Framework for Globally Optimizing Mixed-Integer Signomial Programs

On the Relationship between Power and Exponential Transformations for Positive Signomial Functions

Global optimization of mixed integer nonlinear programming (MINLP) problems containing signomial terms is in many cases a difficult task, and many different approaches to solve these problems have been devised. In Westerlund (2005) a method where a relaxed convex relaxation of the original problem is obtained by approximating single-variable transformations with piecewise linear functions (PLFs...

Binary Image Restoration by Signomial Programming

We present a signomial programming optimization approach to restore binary images which are degraded by additive white Gaussian noise. Numerical experiments confirm the proposed approach is efficient with good accuracy. c © 2007 Optical Society of America OCIS codes: (100.2000) Digital image processing; (100.3020) Image reconstruction-restoration

Global solution of optimization problems with signomial parts

In this paper a new approach for the global solution of nonconvex MINLP (Mixed Integer NonLinear Programming) problems that contain signomial (generalized geometric) expressions is proposed and illustrated. By applying different variable transformation techniques and a discretization scheme a lower bounding convex MINLP problem can be derived. The convexified MINLP problem can be solved with st...