Geometric Programming with Stochastic Parameter

Geometric programming is efficient tool for solving a variety of nonlinear optimization problems. Geometric programming is generalized for solving engineering design. However, Now Geometric programming is powerful tool for optimization problems where decision variables have exponential form. The geometric programming method has been applied with known parameters. However, the observed values of the parameters in real-life GP problems are often imprecise or vague. This data may be different faces such as bounded, interval, fuzzy and random. In this paper, geometric programming with random parameters to be considered. Then stochastic programming has converted to geometric programming with deterministic parameters. By using dual of geometric programming, optimal solutions of stochastic geometric programming can be obtained. Two illustrative examples are presented to demonstrate the efficacy of our method.