01.b. steps of sim study & sim examples_12

8/2/2019 01.B. Steps of Sim Study & Sim Examples_12

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Index

Clarification of terminologies Definition of Simulation Areas of application Examples of Simulation

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Steps in Simulation Study

Flow Chart Problem Formulation

Setting of objectives andoverall project plan

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Data CollectionModel conceptualization

Model Translation

Verified?

Validated?

NoYes

No No

Yes


Flow Chart

Experimental Design

Validated?No No

Yes

Production run &

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More runs??

No

Yes

analysis

Yes

Documentation& reporting

Implementation

Steps in Simulation Study (1/10)

Problem Formulation If the problem statement is provided by the

policy makers, then the analyst must ensure

understood. If the statement is being developed by the

analyst, it is important that the policy makers are agree with the problem.

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Setting of objectives and overall project plan: Objectives indicate the questions to be

answered by the simulation. Overall project plan should include a statement

of the alternative systems to be considered and a method for evaluating the effectiveness of these alternatives.

Overall project plan also includes the plans for number of people involved, the cost of study, number of days required, etc.

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Model conceptualization Start with a simple model and build towards

greater complexity. It is advisable to involve the model user in model

conceptualization it results

enhancement of quality of the model, increase the confidence of model and Also increase the confidence of the model user in the

application of the model.

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Data Collection

Data is dependent upon the complexity of the model

Model Translation Model must be entered into a computer

recognizable format Simulation language: powerful & flexible than

specialized one

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Verified? Is the computer program performing

properly? Wit comp ex mo e , it is i icu t to trans ate

a model successfully in its entirety, without a good deal of debugging.

Common sense is used in completing this step.

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Validated?

Is the determination that the model is an accurate representation of the real system.

Va i ation is usua y ac ieve t roug t e calibration of the model.

Calibration: is an iterative process of comparing the model to the actual system behavior; using the discrepancies between the two, and the insight gained to improve the model.

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Flow Chart

Experimental Design

Validated ?No No

Yes

Production run &

1 May 2012 10

More runs??

No

Yes

analysis

Yes

Documentation& reporting

Implementation


Experimental Design Often the decision concerning the alternatives to

simulate, may be a function of simulation runs (that have been completed and analyzed).

, decisions need to be made, concerning

(i) the length for the initialization period, (ii) the length of simulation runs, (iii) the number of replication to be made of

each run.

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Production runs and analysis It is used to estimate the measures of

performance for the system designs that are .

More runs? Based on the analysis of runs that have been

completed, the analyst determines the number of (additional) runs needed further.

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Documentation and reporting There are two sorts of documentation (i)Program & (ii)Progress (i) Program: It is necessary to explain how the program operates. If the program is to be modified by the same or different analyst,

this should be facilitated b ade uate documentation . In case of changing the parameter clarification needed for how it

effect output by changing the input.

(ii) Progress : Project report give a chronology of work done and decisions made.

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Implementation

It depends upon the previous 11 steps that have been performed.

If the model user has been theoretically involved during the model building process and if the model user understands the nature of the model and its outputs, the likelihood of a vigorous implementation is enhanced.

Conversely, if the model and its underlying assumptions have not been properly communicated, implementation will probably suffer, regardless of the simulation models validity.

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Index

Clarification of terminologies Definition of Simulation Areas of application Examples of Simulation

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SingleChannel Queue (1/10)

A small grocery store has only one check out counter.

Customer arrive at this check out at random from 1 to 8 minutes a art.

Inter arrival time: time between to arrival. This term is used to count arrival event.

Each possible value of inter arrival time has the same probability of occurrence, as shown in the table 1.

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Table 1: Distribution of the time between arrival Ti m e b e t we e nArr i v a l s ( m i n u t e s ) Pr o b ab i l i t y Cu m u l at i v ep ro b a b i l i t y R a n d o m d i g i tAs s i g n m e n t

1 0.125 0.125 001--125

2 0.125 0.250 126250

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3 0.125 0.375 251375

4 0.125 0.500 376500

5 0.125 0.625 501625

6 0.125 0.750 626750

7 0.125 0.875 751875

8 0.125 1.000 876000


The service times vary from 1 to 6 minutes with the probabilities shown in the table# 2;

Table 2: Service time distribution Se rv i c e Ti m e( m i n u t e s )

Pr ob ab i l i t y Cu mu l at iv ep ro b a b i l i t y

R a n d o m d i g i tAs s i g n m e n t

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1 0.10 0.10 01--10

2 0.20 0.30 1130

3 0.30 0.60 3160

4 0.25 0.85 61855 0.10 0.95 8695

6 0.05 1.00 9600


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Number of Customer in the Queue (Graphical representation)

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SingleChannel Queue (10/10)Graphical representation of simulation

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01.b. steps of sim study & sim examples_12

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