SECTION 8
OPTIMIZATION
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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DESIGN STUDY
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What’s in this section:
– Optimization Overview
– Constraints
– Optimization Settings
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION OVERVIEW
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Optimization adjusts design variables to minimize or maximize a
particular aspect of your model’s performance.
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It involves:
– Determining which objective function you want to minimize or maximize,
– Selecting the design variables you want to change, and
– Specifying the constraint functions that must be satisfied.
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Examples of objectives you might want to optimize are:
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Execution time
Energy (effort) required
Total material costs
Comfort
Stability
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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CONSTRAINTS
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Design variables
– Purpose and setup for optimization studies is the same as for design
studies and DOEs.
– By default, Adams/View uses the design variable lower and upper limit (that
is, the range) as constraints for optimization studies.
– You can tell Adams/View to “Allow Optimization to ignore range.”
Note: Only available for DOT or user-defined algorithms.
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Constraint functions
– Setup is analogous to Objective Functions.
– During optimization study, ADAMS/View ensures that evaluated constraint
functions are always negative, and therefore not violated.
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS
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Algorithm types
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Convergence tolerance
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Iterations
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Differencing
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Debugging
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Minimum converged
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS (CONT.)
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Algorithm types
Provided with ADAMS/View
Provided by Design Synthesis, Inc.
User-written algorithms linked to
ADAMS/View
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS (CONT.)
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Algorithm types
– OPTDES_GRG: Uses OPTDES Generalized Reduced Gradient.
– OPTDES_SQP: Uses OPTDES Sequential Quadratic Programming.
Note: These algorithms require that design variables have range limits, because
they work in scaled space.
– DOT1: Use DOT with BFGS (Broydon-Fletcher-Goldfarb-Shanno) for
unconstrained problems; use DOT with MMFD (Modified Method of
Feasible Directions) for constrained problems.
– DOT2: Use DOT with FR (Fletcher-Reeves) for unconstrained problems;
use DOT with SLP (Sequential Linear Programming) for constrained
problems.
– DOT3: Use DOT with FR for unconstrained problems; use DOT with SQP
(Sequential Quadratic Programming) for constrained problems.
For more information on algorithms, see the paper, Numerical Optimization,
which is available in .pdf format from your instructor.
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS (CONT.)
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Convergence Tolerance
– The limit below which subsequent differences of the objective must fall
before an optimization is considered successful.
– Satisfied when:
ABS(objective[new] - objective[new-1]) < convergence tolerance.
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Iterations:
– Maximum
• Tells the optimizer algorithm how many iterations it should take before it admits
failure.
– Rescale
• The number of iterations after which the design variable values are rescaled.
• If you set the value to -1, scaling is turned off.
Note: Option is only available for DOT and user-defined algorithms.
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS (CONT.)
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Differencing
– Technique
• Controls how the optimizer computes gradients for the design functions.
– Increment
• Specifies the size of the increment to use when performing finite differencing to
compute gradients.
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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OPTIMIZATION SETTINGS (CONT.)
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Debugging
– Sends detailed optimizer diagnostics to the window that launched
ADAMS/View.
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Minimum Converged
– The number of consecutive iterations for which the absolute or relative
convergence criteria must be met to indicate convergence.
– Only applicable for the DOT Sequential Linear Programming method.
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For more information on optimization, see the Adams Version 8
Optimization white paper (in .pdf format) and examples.
ADM704a, Section 8 October 2012
Copyright© 2012 MSC.Software Corporation
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WORKSHOP
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Complete Workshop 07: Design of Experiments
ADM704a, Section 8 October 2012
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