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Simulation by Sunaina Dubey
1. SIMULATION
Presented by
Sunaina Dubey
Mba 3rd sem
2. Definition
Steps in simulation
Singnificance of simulation
Techniques of simulation
Example –problem of Monte carlo
simulation and its solution
3. “Simulation is the process of designing a
model of a real system and conducting
experiments with the model for the
purpose of understanding the behaviour
for the operation of the system”
4. In general terms simulation involves
developing a model of some real
phenomenon and then performing an
experiment on the model evolved.It is a
descriptive and not optimisting
techniques.
5. Steps for simulation
Formulation of problem
Introduce important varibles
decision rules of system
parameters
Construct simulation model
Validate the model
Design experiments Modify the modele by
changing the input data
Perform simulation
Is simulation process is
complete?
Select the best course of
action
6. 1. Formulation of problem
2. Introduce important variables decision
rules of system parameters.
3. Construct simulation model
4. Validate the model
5. Design experiments
6. Perform simulation
7. Is simulation problem is complete
8. Select the best course of action
7. To solve cumbersome problem
Experiment
Study the long term effect
To best proposed analytical solution
Stability
Generation of data
Time saving
Last resort
8. Monte carle simulation
Simulation and buisness situation
Simulation and inventory control
Simulation and financial decision
9. Steps:-
1. Establishing probabilty distribution
2. Comulative probability distribution
3. Setting random number intervals
4. Generating random no
10. QUE:- Over 100 days period the daily demands of a certain
commodity shown the following frquency distribution pattern
Daily 0 1 2 3 4 5
demand
No. of 10 20 40 20 6 4 Total
days 100
Using the given data simulate a ten day sequence of the
demands values
11. Solution:-
Daily demand Probabilty=no Cumulative Rendom no
of days/total probability assignment
no of days
0 10/100=0.10 0.10 00-09
1 20/100=0.20 0.30 10-29
2 40/100=0.40 0.70 30-69
3 20/100=0.20 0.90 70-89
4 6/100=0.06 0.96 90-95
5 4/100=0.04 1.00 96-99
How the random no.assignment has been made is very simple to
figure out (on the basis of cumulative frequency)