Personal tools

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.

 

  1. Select the Strategy panel.discrete_strategy1.png
  2. Switch the radio button of the section Strategy for Metamodel-based Optimization to "Sequential with Domain Reduction (SRSM)".

 

 

 

 

 

 

 

 

 

 

 

 

Solvers

Solvers

  1. Select the Solvers panel.discrete_solver1.png
  2. Make sure that the LS-DYNA command matches the one on your computer.
  3. Click the Replace button, if you've made a change.

 

 

 

 

 

 

 

 

 

 

 

Variables

Variables

Modify the Variable thood

  1. Select the Variables panel.
  2. Switch the Type from the variable thood to Discrete Var.
  3. Enter the distinct values in the text box 1 2 3 4 5 (separated by a space).
  4. For Sampling Type select Discrete.

 

 

 

 

 

 

 

 

discrete_variable1.png

Run

Run

Run Panel

  1. Select the Run panel.
  2. For Number of Iterations enter 10.
  3. Push the Run button.

 

 

 

 

 

 

 

 

 

 

discrete_run1.png

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.

 

 ContinuousDiscrete
thood1.5522
tbumper55
HIC125173.4
Mass0.65770.7597
Intrusion550539

Download

Download

The complete data set (input and command files) is available for download:

For Linux

For Windows