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...

In earlier works several data aggregation schemas based methods have been proposed to overcome the problems of the privacy in wireless sensor networks. These methods provides efficient result to analysis of secure data with traditional aggregation because cluster heads can straightforwardly comprehensive the cipher texts not including decryption; accordingly, reduces the transmission overhead i...

Convex optimization has provided both a powerful tool and an intriguing mentality to the analysis and design of communication systems over the last few years. A main challenge today is on nonconvex problems in these application. This paper presents an overview of some of the important nonconvex optimization problems in point-to-point and networked communication systems. Three typical applicatio...

Nonlinear convex optimization has provided both an insightful modeling language and a powerful solution tool to the analysis and design of communication systems over the last decade. A main challenge today is on nonconvex problems in these applications. This chapter presents an overview on some of the important nonconvex optimization problems in communication networks. Four typical applications...

With the increasing reliance on modeling optimization problems in practical applications, a number of theoretical and algorithmic contributions of optimization have been proposed. The approaches developed for treating optimization problems can be classified into deterministic and heuristic. This paper aims to introduce recent advances in deterministic methods for solving signomial programming p...

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...

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