Solution with LS-OPT
Solution with LS-OPTui
Solution with LS-OPTui
Strategy
- Select the Strategy panel.
- Choose Single Stage for Strategy for Metamodel-based Optimaization.
Solvers
Prepare the input file AnalysisResults.csv.
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Variables
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Sampling
- Select the Sampling panel.
- For METAMODEL select from the list Radial Basis Function Network.
- For POINT SELECTION we choose Space Filling. (Actually, the ways of point selection make no difference in this instance, since only the points defined in AnalysisResults.csv will be taken.)
Responses
- Select the Responses panel.
- From the list on the right side we can see that the responses are already defined. Actually, like the variables, the responses are automaitcally associated with the correct analysis case from the .csv file.
Repair
- From the menu bar select
Task→Repair.
- It turns automatically to the Run panel.
Select Import result (.csv).
- Push the Run button. (Save the project as com.repair.readuserresults)
Task
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Objective
- Select the Objective panel.
- From Response select HIC as the objective.
- For Weight leave the default 1. If you have several objective functions, you may assign weight to each one according to their importance.
Contraints
- Select the Responses panel.
- From the possible response types select: Composite-Expression.
- Enter the expression Disp1-Disp2.
- For Response Name enter Intrusion.
- Push the Add button.
- Select the Constraints panel.
- From Response select Intrusion as the constraint.
- For Upper Bound enter 550.
Run
- Select the Run panel.
- Select Omit Last Verification Run.
- Push the Run button. (Save the project as com.userresults)
Com-file
The created command file may look like this:
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
Command file "com.userresults.correct"
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ Generated using LS-OPT Version 4.1
$
"Optimization Problem"
$
$ Created on Fri Apr 1 13:25:51 2011
solvers 1
responses 5
$
$ NO HISTORIES ARE DEFINED
$
$
$ DESIGN VARIABLES
$
variables 2
Variable 'tbumper' 3.
Lower bound variable 'tbumper' 1.
Upper bound variable 'tbumper' 5.
Variable 'thood' 1.
Lower bound variable 'thood' 1.
Upper bound variable 'thood' 5.
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ OPTIMIZATION METHOD
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
Optimization Method SRSM
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ SOLVER "1"
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
$ DEFINITION OF SOLVER "1"
$
solver dyna960 '1'
solver response user "AnalysisResults.csv"
solver check output on
solver compress d3plot off
$ ------ Pre-processor --------
$ NO PREPROCESSOR SPECIFIED
$ ------ Post-processor --------
$ NO POSTPROCESSOR SPECIFIED
$ ------ Metamodeling ---------
solver order RBF
solver experiment design space_filling
solver update doe
$ ------ Job information ------
$
$ RESPONSES FOR SOLVER "1"
$
response 'Disp2' 1 0 "AnalysisResults.csv"
response 'Disp1' 1 0 "AnalysisResults.csv"
response 'Acc_max' 1 0 "AnalysisResults.csv"
response 'Mass' 1 0 "AnalysisResults.csv"
response 'HIC' 1 0 "AnalysisResults.csv"
composites 1
$
$ COMPOSITE EXPRESSIONS
$
composite 'Intrusion' {Disp1-Disp2}
$
$ OBJECTIVE FUNCTIONS
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objectives 1
objective 'HIC' 1
$
$ CONSTRAINT DEFINITIONS
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constraints 1
constraint 'Intrusion'
strict
upper bound constraint 'Intrusion' 550
$
$ PARAMETERS FOR METAMODEL OPTIMIZATION
$
Metamodel Optimization Strategy SINGLESTAGE
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iterate param design 0.01
iterate param objective 0.01
iterate param stoppingtype and
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$ OPTIMIZATION ALGORITHM
$
Optimization Algorithm hybrid simulated annealing
Use GSA
$
$ JOB INFO
$
iterate noverify
iterate 0
STOP
Results
Results
Download
The complete data set (input and command files) is available for download:
For Linux
For Windows
