Disciplined geometric programming

Disciplined Convex Programming∗

Convex programming is a subclass of nonlinear programming (NLP) that unifies and generalizes least squares (LS), linear programming (LP), and convex quadratic programming (QP). This generalization is achieved while maintaining many of the important, attractive theoretical properties of these predecessors. Numerical algorithms for solving convex programs are maturing rapidly, providing reliabili...

Geometric Programming with Stochastic Parameter

Geometric programming is efficient tool for solving a variety of nonlinear optimizationproblems. Geometric programming is generalized for solving engineering design. However,Now Geometric programming is powerful tool for optimization problems where decisionvariables have exponential form.The geometric programming method has been applied with known parameters. However,the observed values of the ...

Disciplined Multi-core Programming in C

The problem of programmability on modern heterogeneous multi-core and future many-core embedded platforms is still not solved satisfactorily: although many existing but incompatible approaches do provide new languages, language extensions and library interfaces that all focus on specific solutions, and powerful analytical models do exist, no single integrated programming model has been proposed...

Geometric Programming Problem with Trapezoidal Fuzzy Variables

Nowadays Geometric Programming (GP) problem is a very popular problem in many fields. Each type of Fuzzy Geometric Programming (FGP) problem has its own solution. Sometimes we need to use the ranking function to change some part of GP to the linear one. In this paper, first, we propose a method to solve multi-objective geometric programming problem with trapezoidal fuzzy variables; then we use ...

Geometric Programming