relevance of simulation models for assessments of livinglabs activity university of maribor faculty...
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Relevance of Simulation Models for
Assessments of LivingLabs Activity
University of MariborFaculty of Organizational Sciences
www
http://kib1.fov.uni-mb.si
Cybernetics & DSS Laboratory
e-mail: [email protected]
Miroljub Kljajić, Professor & Head
Laboratory of Cybernetics and Decision Support Systems
University of Maribor, Faculty of Organizational Sciences
IntroductionIntroduction
• 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 multi-level 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..
Cybernetics & DSS Laboratory
statical
laboratory
operational gam e continuous (analog)
discrete (d igital)sim ulation “m an-m achine”
sim ulation
dynam ical sta tical dynam ical (numerica l, analytica l)
com puter
physical m athem atica l
m odels
Model Classification (Forrester,1961)
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.
R esultsRank o f
A lternativesS im ulation
M odelBus inessDa tabase
G SS
ESScenarios
Case 1: VIM Models Screen Capture of Production Line SelectionKljajić, 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
Forecast of the Cumulative production (X1, X2, X3, X4) and real production in the first four years
0
10000
20000
30000
40000
50000
60000
1999 2000 2001 2002
Year
Pro
du
ctio
n [
PU
/Yea
r]
X1
X2
X3
X4
Real
Post-Decision Analysis of Production Line Selection
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;
Tim e [M on th ]
Net
Inco
me
[MU
]
0 20 40 60 80 100
0
1,000
2,000
3,000
1
5
5
4
1
2
3
5
t0
Post-Decision Analysis of Production Line Selection
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
Tim e [M on th ]
Net
Inco
me
[MU
]
0 20 40 60 80 100
0
1,000
2,000
3,000
5E V
t0
Time[Month]
Net
Inc
ome
[MU
]
0 20 40 60 80
-2,000
-1,000
0
1,000
2,000
1 2 3 1 2
31 2
3
1 2
3
1
2
3
EV Vs A4 Analysis
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
t0
Expected
Value
Cybernetics & DSS Laboratory
Case 2: THE ROLE OF INFORMATION FEEDBACK IN THEMANAGEMENT GROUP DECISION-MAKING PROCESS APPLYINGSYSTEM DYNAMICS MODELSŠkraba, 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.
YUM
XD G
a 3a 2
J( Y, U )
a 1
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
Cybernetics & DSS Laboratory
GS
S1
If
S2 Sn
ISn1 ISn2 ISn. . .
. . .
...
...
Structure of the Group Feedback Interaction
Comparing Methods
Cybernetics & DSS Laboratory
Val
ue o
f crit
eria
func
tion
(J)
a 1
a 2
a 3-1 .5
-1.0
-0.5
0.5
0.0
1.0
1.5
R ank
0 10 20 30 40 50 60
Condition a2 , 4 Phases
a 2 1
a 2 2
a 2 3
a 2 4
-0 .25
-0.50
0
0.25
0.50
0.75
1.00
1.25
1.50
Val
ue o
f crit
eria
func
tion
(J)
N um ber of S ubjects
0 10 20 30 40 50 60
Condition a3 , 4 Phases
a 3 1
a 3 2
a 3 3
a 3 4
-0.25
-1.30
0
0.25
0.50
0.75
1.00
1.25
1.50
Val
ue o
f crit
eria
func
tion
(J)
R ank
0 10 20 30 40 50 60
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.