Optimization
Optimization searches for new parameter values that will drive multiple response values to desired targets. This is accomplished by defining a range of feasible values for each parameter (continuous, integer, or discrete) and by defining constraints and goals for the statistics (mean, standard deviation, and/or probability of non-compliance) of each response. Optimization thus enables you to identify the parameter values that achieve the right balance between performance, quality, reliability and cost across multiple responses.
Features:
- Discover new designs (combinations of parameter values) that have higher performance, higher quality, lower cost, or all of the above
- Discover designs that are robust to parameter variability
- Easy-to-use and learn interface
- Unlimited numbers of factors, responses, goals and constraints*
- Extremely robust custom genetic algorithm for truly multi-objective, nonlinear, statistical, global optimization
- Mixed continuous/ integer/discrete search
- Full support of index variables and table lookup searches
*Constrained only by worksheet size/memory limits in MS Excel™
Screenshots:
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