Automated Variable and Tradespace Analysis for Your Simulation Tool

Users of simulation models rarely know which input parameters have the greatest influence on the system they are modeling.  Often they do not know which combinations of parameters lead to the best and worst performance of their system.

OptTek tools contain libraries that provide a suite of analysis tools to automate the discovery of influential variables, to identify and characterize multiple good and bad regions of the model tradespace, and to classify the robustness of point solutions and regions.  These tools are used is used with simulation models or other data sets that contain a collection of input values and corresponding response values.  Our tools work over a diverse set of variable types including binary, integer, continuous, discrete, enumerated, and categorical variables.  The software libraries provide automated insights for customers who may have limited knowledge of how statistical analysis and data mining works yet who desire access to sophisticated analytic techniques.

Following an OptQuest driven search, or with a collection of model inputs and responses derived from another source, our software analyzes the data and draws insights from it by running its suite of multivariate analysis tools.  The tools draw on techniques such as regression, variable effects, regression trees, patient rule induction method, and clustering, and other data mining techniques.

The state-of-the-art analytics tools embedded in our software are used to create easy to digest displays highlighting influential variables, good and bad regions of the model tradespace, and the robustness of point solutions and regions. Our tools key insights and increases the return on investment of your simulation studies.