Discrete optimization
Solving the optimization problem with a discrete variable.
Solution with LS-OPTui
Solution with LS-OPTui
Strategy
Strategy
Load the com.linear.single file you created in the first part or download the input file above.
- Select the Strategy panel.

- Switch the radio button of the section “Strategy for Metamodel-based Optimization” to "Sequential with Domain Reduction (SRSM)".
Solvers
Solvers
- Select the Solvers panel.
- Make sure that the LS-DYNA command matches the one on your computer.
- Click the Replace button, if you've made a change.
Variables
Variables
Modify the Variable thood
| ![]() |
Run
Run
Run Panel
| ![]() |
Com-file
Com-file
The created command file may look like this:
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
Command file "com.linear.single"
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ Generated using LS-OPT Version 4.1
$
"Optimization Problem"
$
$ Created on Fri Jan 7 12:20:34 2011
solvers 1
responses 5
$
$ NO HISTORIES ARE DEFINED
$
$
$ DESIGN VARIABLES
$
variables 2
Variable 'tbumper' 3.
Lower bound variable 'tbumper' 1.
Upper bound variable 'tbumper' 5.
Variable 'thood' 1.
Variable 'thood' discrete {1 2 3 4 5}
Variable 'thood' use discrete
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ OPTIMIZATION METHOD
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
Optimization Method SRSM
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$ SOLVER "1"
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
$ DEFINITION OF SOLVER "1"
$
solver dyna960 '1'
solver command "ls971_R4_2"
solver input file "main.k"
solver check output on
solver compress d3plot off
$ ------ Pre-processor --------
$ NO PREPROCESSOR SPECIFIED
$ ------ Post-processor --------
$ NO POSTPROCESSOR SPECIFIED
$ ------ Metamodeling ---------
solver order linear
solver experiment design dopt
$ ------ Job information ------
solver concurrent jobs 1
$
$ RESPONSES FOR SOLVER "1"
$
response 'Disp2' 1 0 "BinoutResponse -res_type Nodout
-cmp x_displacement -id 432 -select TIME "
response 'Disp1' 1 0 "BinoutResponse -res_type Nodout
-cmp x_displacement -id 167 -select TIME "
response 'MaxAccel' 1 0 "BinoutResponse -res_type Nodout
-cmp x_acceleration -id 167 -select MAX -start_time 0.0000 -filter SAE -filter_freq 60.0000"
response 'HIC' 1 0 "BinoutResponse -res_type Nodout
-cmp HIC15 -units S -lengthunits MM -id 432"
response 'MASS' 1 0 "DynaMass 2 3 4 5 MASS"
composites 1
$
$ COMPOSITE RESPONSES
$
composite 'Intrusion' type weighted
composite 'Intrusion' response 'Disp2' -1 scale 1
composite 'Intrusion' response 'Disp1' 1 scale 1
$
$ OBJECTIVE FUNCTIONS
$
objectives 1
objective 'HIC' 1
$
$ CONSTRAINT DEFINITIONS
$
constraints 1
constraint 'Intrusion'
upper bound constraint 'Intrusion' 550
$
$ PARAMETERS FOR METAMODEL OPTIMIZATION
$
Metamodel Optimization Strategy DOMAINREDUCTION
$
iterate param design 0.01
iterate param objective 0.01
iterate param stoppingtype and
$
$ OPTIMIZATION ALGORITHM
$
Optimization Algorithm hybrid simulated annealing
Use GSA
$
$ JOB INFO
$
iterate 10
STOP
Results
Results
The method of viewing the results is completely the same as in the other two cases.
We compare the results of the continuous and discrete analysis and list them in the table below.
| Continuous | Discrete | |
| thood | 1.552 | 2 |
| tbumper | 5 | 5 |
| HIC | 125 | 173.4 |
| Mass | 0.6577 | 0.7597 |
| Intrusion | 550 | 539 |
Download
Download
The complete data set (input and command files) is available for download:
For Linux
For Windows


