Lecture16_Process Analyzer and OPTQUEST.ppt

USING Arena - Simulation 5
Using Optquest
LECTURE 16
1
Prof. Rifat Rustom
Prof. of Civil Engineering at the Islamic University of Gaza
Rector – University College of Applied Sciences

Lecture Objectives
Practice models _ Simulation with Arena
C1/2
Optimization of
number of
resources used
Optimization of
Total System
Costs (Entities
Cost and
Resources Cost)
1 2
Demonstrate
the following
concepts and
modules in
modeling
optimum
operations
using Optquest:

Process
Analyzer
Practice models _ Simulation with Arena
C1/2
The Process Analyzer (PAN) assists in the
evaluation of alternatives presented by the
execution of different simulation model
scenarios.
The Process Analyzer is focused at post-
model development comparison of models
after the simulation model is complete,
validated, and configured appropriately for
use by the Process Analyzer.
The role of the Process Analyzer is to allow
for comparison of the outputs from validated
models based on different model inputs.
1
2
3

Simulation with Arena Chapter 5 – Detailed Modeling and Terminating Statistical Analysis Slide 4 of 88
Evaluating Many Alternatives with the Process Analyzer (PAN)
• With (many) more than two alternatives to compare, two problems are
 Simple mechanics of making the possibly many
parameter changes, making the runs, keeping track of
the many output files
 Statistical methods for drawing reliable and useful
conclusions
• PAN operates on program (.p) files – produced when .doe file is run (or
just checked)
• Start PAN from Arena (Tools/Process Analyzer) or via Windows
• PAN runs on its own, separate from Arena

PAN Scenarios
• A scenario in PAN is a combination of:
A program (.p) file
Set of input controls that you choose
– Chosen from Variables and Resource capacities – think ahead
– You fill in specific numerical values
Set of output responses that you choose
– Chosen from automatic Arena outputs or your own Variables
– Values initially empty … to be filled in after run(s)
To create a new scenario in PAN, double-click where indicated, get
Scenario Properties dialog
– Specify Name, Tool Tip Text, .p file, controls, responses
– Values of controls initially as in the model, but you can change them in PAN – this is the real utility of PAN
– Can duplicate (right-click, Duplicate) scenarios, then edit for a new one
Think of a scenario as a row

PAN Projects and Runs
• A project in PAN is a collection of scenarios
 Program files can be the same .p file, or .p files from different model .doe files
 Controls, responses can be the same or differ across scenarios in a project –
usually will be mostly the same
 Think of a project as a collection of scenario rows – a table
 Can save as a PAN (.pan extension) file
• Select scenarios in project to run (maybe all)
• PAN runs selected models with specified controls
• PAN fills in output-response values in table
 Equivalent to setting up, running them all “by hand” but much easier, faster, less
error-prone

Running Model 5-3 with PAN
• Scenarios
 Base case (no additional resources)
 Imagine $1200/week to spend on each additional resource type, one at a time (no
mixed enhancements)
 7 scenarios in all (details in book)
 Select all to run (click on left of row, Ctrl-Click or Shift-Click for more)
 To execute, or Run/Go or F5

Statistical Comparisons with PAN
• Model 5-3 alternatives were made with 10 replications each
 Better than one replication, but what about statistical validity of comparisons,
selection of “the best”?
• Select Total Cost column, Insert/Chart (or or right-click on column, then Insert Chart)
 Chart Type: Box and Whisker
 Next, Total Cost; Next defaults
 Next, Identify Best Scenarios
– Smaller is Better, Error Tolerance = 0 (not the default)
– Show Best Scenarios; Finish

Statistical Comparisons with PAN (cont’d.)
• Vertical boxes: 95%
confidence intervals
• Red scenarios
statistically
significantly better
than blues
 More precisely, red
scenarios are 95% sure
to contain the best one
 Narrow down red set –
more replications, or
Error Tolerance > 0
 More details in book

Process Analyzer- Example 2
Lecture 16 C1/10
Objective:
Run the system at different Capacity
of Resources and compare the total
system Cost.

Lecture 16 C1/11
Open PAN:
in Arena:
Now that you have Process Analyzer
open:
 Select File > New
 Follow the direction and Double-click
here to add a new scenario
 Select Tools > Process Analyzer

Lecture 16 C1/12
Add a New Scenario:
To add a new scenario, the Scenario
Properties dialog is used to specify the
Arena model file (*.p) that will be used in
the scenario.
 Press Browse
 Find your file ModelFile.p
 Press OK

Lecture 16 C1/13
Open Model File:
 Process Analyzer example 2.p

Lecture 16 C1/14
Specify Controls,
Responses and
Scenarios
We will make the number of Loader a control and
Select Insert > Control
 Expand the Resource list of Controls
 Select the name of Loader resource
 Press OK
The control is added and set to the default

Lecture 16 C1/15
Responses
The response will be our System Cost statistic.
 Select Insert > Response
 Expand the User Specified list of Responses
 Select the name of your response
 Press OK

Lecture 16 C1/16
Running and Graphing the
Results
To run the scenarios, select the rows of the
scenarios you want to run and press run.
 Click on the 1 to the left of Scenario 1
 Hold down the Shift key and click on the 1
to the left of Scenario 2
 Select Run > Go
 Press OK in the dialog box that appears
This will take a while. You can see the count
of the number of replications performed for
each scenario.

Lecture 16 C1/17
Running and Graphing the
Results
To see the results, compare the minimum
System. Total Cost values

Lecture 16 C1/18
Graphing the Results
 Select the Response column System.
Total Cost
 Select Insert > Chart
 Select a Box and Whisker chart
 Press Next three times
 Check the box Identify Best Scenario

C1/2
OptQuest® for Arena®
Allows to model and experiment
with several alternative scenarios
so that you can select the one
that best meets your objectives

Optquest- Example 3
Lecture 16 C1/20
Objective:
Determine the Capacity of Resources
used to optimize the total system
Cost (Loader 1, Loader 2 ?)

Optquest- Example 3
Lecture 16 C1/21
1. Define Controls:
Select the resources and
determine their bounds of
the Capacity of Resources
used
• Loader 1 (from 1 to 8)
• Loader 2 (from 1 to 8)

Optquest- Example 3
Lecture 16 C1/22
2. Define Responses
(Output):
Select the output values that need to
be determined based on the
optimum solution
• Choose System Total Cost

Optquest- Example 3
Lecture 16 C1/23
4. Add Objectives:
Add new Objective

Optquest- Example 3
Lecture 16 C1/24
5. Define Objectives:
Select the expression that
needs to be optimized
• Choose System.Total Cost
• Select Minimize

Optquest- Example 3
Lecture 16 C1/25
6. Define Options:
• Stop options
• Tolerance
• Replications

Optquest- Example 3
Lecture 16 C1/26
7. Optimize:
Run the optimization

Optquest- Example 3
Lecture 16 C1/27
8. Suggested Best Solutions
(Output):
View the best output values based
on the optimization process

Optquest- Example 3
Lecture 16 C1/28
9. Optimal Solution:
Determine the Best value of:
• Objective
• Controls

Optquest- Example 3
Lecture 16 C1/29
10. Re-run the Model:
Re-run the model based
on the Best value of
Controls (Loader 1 = 1,
Loader 2 = 4) to analyze
the output.

Optquest- Example 4
Lecture 16 C1/30
Objective:
Determine the Capacity
of Resources used to
optimize the total
system Cost (Loader 1,
Loader 2 ?) and Time of
Run when the number
of trucks to be
processed = 1000

Optquest- Example 4
Lecture 16 C1/31
9. Optimal Solution:
Determine the Best value of:
• Objective
• Min (Total System Cost)
• Min (Time of Run)
• Controls

Optquest- Example 4
Lecture 16 C1/32

Lecture16_Process Analyzer and OPTQUEST.ppt

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