Solving The Optimization Problem Of The Independent Variables

962 Words Aug 24th, 2015 4 Pages
In this section, we provide details of the four modules of this invention. However, any one module of this invention can’t solve our problem alone. It is the interaction of all parts that allow the user to understand and improve the optimization models.
We begin by defining the optimization problem. Our objective is to maximize or minimize the sum of objective terms by selecting optimal feasible levels of the independent variables. The set of process limits or constraints define the feasible region. For example, upper and lower limits on the independent variables are constraints on the problems. Additionally, there are dependent variables that aid in defining the objective terms and/or constraints. These dependent variables are functions of the independent variables. A glossary of terms can be found in Appendix A.
This invention consists of four interaction modules,
(1) Shadow value analysis. Systematically breaking down the optimality conditions of the problem into understandable pieces.
Anthony Ciravolo, J.D. Terry, Ken Tyner, Bill Docter, John Righi, Joseph Evans, Narendranath Y. Gaitonde

A crucial step in understanding an optimization solution is interpreting the tradeoffs that an optimization solver makes. Shadow value analysis conveys variable interactions to the user through the eyes of the optimizer. To this end, this invention systematically breaks down the equations or conditions that are needed to define the optimal solution. In doing this, the user…

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