A very useful multi-objective technique is goal programming. There are many methodologies of goal programming such as weighted goal programming, min-max goal programming, and lexicographic goal programming. In this paper, weighted goal programming is reformulated as goal programming with logarithmic deviation variables. Here, a comparison of the proposed method and goal programming with weighte...

Geometric programming is a new optimization technique developed to solve nonlinear engineering design problems subject to either linear or nonlinear constraints. This paper outlines the procedure and illustrates its use with a series of examples. These examples include a compressor design, and a compressor transmission line problem. Geometric programming solutions not only yield optimal design ...

In applications of geometric programming, some coefficients and/or exponents may not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which stochastic programming approaches and which structural and distributional assumptions do not destroy the favorable structure of geometric programs. The already recognized possibi...

In this paper, single and multi container maintenance model under limited time interval of interest is introduced in fuzzy environment. These fuzzy models are solved by fuzzy geometric programming technique. Here fuzzy geometric programming is discussed through fuzzy decision-making processes with three different operators, max-min, max-average mean, and max-geometric mean. These operators are ...

This paper shows how the fundamental geometric inequality lemma of geometric programming can be obtained immediately from information theoretic methods. This results in a drastic simplification of the proof and points the way to other connections between information theory and geometric programming