With the increasing reliance on modeling optimization problems in practical applications, a
number of theoretical and algorithmic contributions of optimization have been proposed. The …

Various optimization problems in engineering and management are formulated as nonlinear
programming problems. Because of the nonconvexity nature of this kind of problems, no …

This paper presents a global optimization approach for solving signomial geometric
programming problems. In most cases nonconvex optimization problems with signomial …

This study proposes a novel approach for finding the exact global optimum of a mixed-
discrete structural optimization problem. Although many approaches have been developed …

Many global optimization approaches for solving signomial geometric programming
problems are based on transformation techniques and piecewise linear approximations of …

In this paper, we present a global optimization method for solving nonconvex mixed integer
nonlinear programming (MINLP) problems. A convex overestimation of the feasible region is …

Aposynomial geometric programming problem is composed of a posynomial being
minimized in the objective function subject to posynomial constraints. This study proposes …

Generalized geometric programming (GGP) problems consist of a signomial being
minimized in the objective function subject to signomial constraints, and such problems have …

Signomial geometric programming (SGP) is a computationally challenging, NP-Hard class of
nonconvex nonlinear optimization problems. SGP can be solved iteratively using a …

Posynomial terms frequently appear in many nonlinear problems and are the core
components of geometric and generalized geometric programming problems. The most …