University of Maribor
Faculty of Organizational Sciences
Relevance of Simulation Models for
Assessments of LivingLabs Activity
Miroljub Kljajić, Professor & Head
Laboratory of Cybernetics and Decision Support Systems
University of Maribor, Faculty of Organizational Sciences
Cybernetics & DSS Laboratory
www
e-mail: [email protected]
http://kib1.fov.uni-mb.si
Introduction
•
Basic Definition
•
Complex systems
•
Living Systems
•
Simulation model
•
Living Labs model
System
•
•
•
System means a whole consist of parts and was
the axiom for ancient philosophers.
A system is composed of regularly interacting or
interdependent groups of activities/parts that
form the emergent whole.
Complex systems are phenomenon consisting of
a large number of elements organized in a multilevel hierarchical structure where elements
themselves could represent systems (Mesarovic,
1989).
System (contd.)
•
Living Systems Theory is a general theory about
how all living systems "work," about how they
maintain themselves and how they develop and
change (J G Miller, 1978).
•
Living systems can be as simple as a single cell
or as complex as a supranational organization
(such as the European Economic Community).
•
System dynamics is a method for understanding
the dynamic behavior of complex systems. The
basic method in studding complex system is the
modeling and simulation..
Model Classification (Forrester,1961)
models
physical
statical
mathematical
dynamical
statical
dynamical (numerical, analytical)
simulation
laboratory
computer
operational game
continuous (analog)
simulation “man-machine”
discrete (digital)
Cybernetics & DSS Laboratory
Living LabsSim = Operation game.
•
Computer system users, administrators, and designers usually
have a goal of highest performance at lowest cost. Modeling and
simulation of system design trade off is good preparation for
design and engineering decisions in real world jobs (Arsham,
2005).
•
Dynamic modeling in organizations is the collective ability to
understand the implications of change over time.
•
Another important application of simulation is in developing
"virtual environments" , e.g., for training military personnel for
battlefield situations, disaster relief, etc..
Simulation Approach to Decision
Assessment in Living Labs
•
The use of visual interactive modeling and animation can help
users to obtain a better understanding of simulation results,
especially those, who are not computer simulation experts.
Decision-makers are motivated by the animation while seeking
better solutions for complex problems.
GSS
Business
Database
Simulation
Model
Results
ES
Scenarios
Rank of
Alternatives
Case 1: VIM Models Screen Capture of Production
Line Selection
Kljajić, M., Bernik, I., & Škraba, A. (2000). Simulation Approach to Decision Assesment in Enterprises.
Simulation, 75 (4), Simulation Councils Inc., 199-210.
Video
Variants:
Post-Decision Analysis of Production
Line Selection by Simulation Methods
60000
Production [PU/Year]
50000
40000
X1
X2
30000
X3
X4
20000
Real
10000
0
1999
2000
2001
2002
Year
Forecast of the Cumulative production (X1, X2, X3, X4) and
real production in the first four years
Post-Decision Analysis of Production
Line Selection
Net Income [MU]
3,000
3
2,000
1
2
5
5
1,000
5
0
1
4
0
20
40
t0 60
80
100
Time[Month]
Figure 6a): Comparison of the Predicted Net Income under different scenarios (Curves 1, 2, 3,
4) and realized Net Income (Curve 5) for the first 48 months with its predicted values until 96
months;
Post-Decision Analysis of Production
Line Selection
Net Income [MU]
3,000
2,000
EV
5
1,000
0
0
20
40
t0 60
80
100
Time[Month]
Figure 6b): Expected Value of Net Income EV and realized Net Income
(Curve 5) for the first 48 months and its predicted values until 96 months
Net Income [MU]
EV Vs A4 Analysis
Expected
Value
2,000
1,000
01 2
3
12
3
12
12
1
2
3
-1,000
3
-2,000
0
20
40
t0
60
3
80
Time[Month]
Expected Value (EV) (Curve 1) for the first 48 months, Realized Net
Income (Curve 2) and the fully automated production process i.e.
alternative A4 outcome (Curve 3) i.e. highest financial risk
Case 2: THE ROLE OF INFORMATION FEEDBACK IN THE
MANAGEMENT GROUP DECISION-MAKING PROCESS APPLYING
SYSTEM DYNAMICS MODELS
Škraba, A., Kljajić, M., & Leskovar, R. (2003). Group exploration of system dynamics models – Is there a place
for a feedback loop in the decision process? System Dynamics Review, 19, 243-263.
a1 a2 a3
X
DG
U
M
Y
J(Y, U)
Cybernetics & DSS Laboratory
System Elements and Experimental Conditions
•
M ~ Model i.e. Business simulator
•
DG ~ Decision Group
•
a1 ~ Individual decision-making without the simulation model
•
a2 ~ Individual decision-making supported by the simulation
model
•
a3 ~ Decision-making supported by both the simulation model
and group feedback information
Structure of the Group Feedback Interaction
GS
S2
ISn1
ISn2
.
.
.
S1
.
.
.
.
.
.
If
Sn
ISn
.
.
.
Cybernetics & DSS Laboratory
Comparing Methods
1.5
Value of criteria function (J)
1.0
0.5
0.0
-0.5
-1.0
-1.5
0
10
20
30
40
50
60
a1
a2
a3
Rank
Cybernetics & DSS Laboratory
Condition a2 , 4 Phases
1.50
Value of criteria function (J)
1.25
1.00
0.75
0.50
0.25
0
-0.25
-0.50
0
10
20
30
Number of Subjects
40
50
60
a 21
a 22
a 23
a 24
Condition a3 , 4 Phases
1.50
Value of criteria function (J)
1.25
1.00
0.75
0.50
0.25
0
-0.25
-1.30
0
10
20
30
Rank
40
50
60
a 31
a 32
a 33
a 34
Conclusion
•
Simulation, supported with animation, which demonstrates the
operations of the modeled system, helps participants to
recognize the specifics of the presented system.
•
Decision-makers are motivated by the animation of a real
system, due to the cognitive information obtained, which is
relevant for model validation.
•
Such simulations are used extensively today to train military
personnel for battlefield situations, reengineering process,
development of new products, integrated modeling and
simulation environments etc.