Optimize your designs
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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.


  • 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™


At its heart, optimization is nothing more than a tool to help people make decisions. For any decision we want to identify the best solution from a set of many different possible alternatives. For determining what is “best” we almost always have several criteria. These criteria often conflict, and some criteria are more important than others.

We perform an optimization by defining the range of different solution alternatives, defining the criteria for evaluating them, and then having an optimization algorithm perform an automated, intelligent search.

Alternatives are represented mathematically as specific values for one or many parameters.

Criteria are divided into two groups: those that must be satisfied and those that ideally should be satisfied. Criteria that must be satisfied are called Constraints, and criteria that ideally are satisfied are called Goals. Each constraint and goal is represented by its own response equation.


  • Microsoft Windows 7, 8, 10, 11
  • Microsoft Excel 2013, 2016, 2019, 365
  • WARNING: SDI Tools does not support these versions of Office 365 (Office from Microsoft Store, Office Online, Office for Mac, Office for iOS)
  • Administrator rights required to install software


  • Define input parameters as: Continuous, Integer, Discrete, Noise, Constant


  • Probability distributions can be defined as: Normal, Uniform, Triangular, Lognormal, Exponential, Weibull, Beta, Gamma, Johnson, or Histogram.
  • Multiple distributions can be combined and/or truncated to create unique composite distributions.


  • Define the lower and/or upper specification limits for each output response.
  • Define the Probability of Non-Compliance (PNC) goal.


  • Define constraints in terms of Mean Value, Standard Deviation, and Probability of Non-Compliance (PNC).
  • Constraints can be Greater Than or Equal To, Equal To, or Less Than or Equal To a specified value or cell.


  • Define goals in terms of Mean Value, Standard Deviation, and Probability of Non-Compliance (PNC).
  • Goals can be Greater Than or Equal To, Equal To, or Less Than or Equal To a specified value or cell.
  • Assign a Priority Level or Weight to each goal.


  • Define input parameters and output responses on Excel worksheets.
  • Define indicators of each cell type


  • Quickly modify the problem using the Formulation Editor.


This video shows Optimization using SDI Tools v3 in action. We will be updating this video to reflect changes to SDI Tools v4 soon.

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SDI Tools 4.13.2 is available