Stochastic Geometric Programming: Approaches and Applications

During the last years, an increasing interest in geometric programming (GP) can be observed. Advances in numerical methods allow to solve large GPs and new areas of successful applications have emerged: besides of technical applications, there are also GPs for optimal production planning, finance, etc. In real-life applications of GP, some of coefficients and/or exponents need not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which of general stochastic programming techniques and under which structural and distributional assumptions do not destroy the favorable structure of GPs. Both the already recognized and new approaches will be presented in connection with formulation of the optimization problem. The short note below should serve as an introduction to basic concepts and references.