This document provides an introduction and overview of simulation modeling. It discusses when simulation is an appropriate tool, the advantages and disadvantages, common applications, and the basic components and types of systems that can be modeled. It also outlines the typical steps involved in a simulation study, including problem formulation, model building, experimentation and analysis, and documentation. Model building involves conceptualizing the model, collecting data, translating the model into a computer program, verifying that the program is working correctly, and validating the model outputs against real system behavior.

1. Introduction to simulation
UNIT 1 (CHAPTER 01)
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2. contents
 When simulation is the appropriate tool and when it is not appropriate
 Advantages and disadvantages of Simulation
 Areas of application
 Systems and system environment
 Components of a system
 Discrete and continuous systems
 Model of a system
 Types of Models
 Discrete-Event System Simulation
 Steps in a Simulation Study
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3. What is simulation?
 Definition: It is the imitation of the operation of a real world process or system over
time.
 It involves the generation of artificial history of the system and the observation of that
artificial history to draw the inferences concerning to the characteristics of the real
system.
 The behavior of a system as it evolves over time is studied by developing simulation
model.
 Simulation modeling can be used both as an analysis tool and a design tool.
 Analysis Tool: To predict the effect of changes to the existing systems
 Design Tool: To predict the performance of new systems under varying sets of
circumstances.
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4. When simulation is an appropriate tool?
 To study the internal interactions of a computer system or a subsystem within a complex
system.
 To study the informational, organizational and environmental changes which affects the
model’s behavior.
 To gain the knowledge which may help to investigate the improvement of a model
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5. When simulation is an appropriate tool?
Cont’d
 Changing the simulation i/p’s and studying the o/p’s can produce a valuable insight
 Can be used as pedagogical device to reinforce analytical solution methodologies
 Can be used to experiment with new designs or policies before implementation to prepare
what might happen.
 To verify analytic solutions.
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6. When simulation is an appropriate tool?
Cont’d
 Simulating different capabilities can determine the requirements on it.
 Animation shows a system in simulated operation can be visualized.
 To study the modern systems.
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7. When Simulation is not appropriate?
 Should not be used when the problem can be solved with common sense
 Should not be used when the problem can be solved analytically.
 Should not be used if it is easier to perform the direct experiments.
 Not to use simulation if costs exceeds the savings.
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8. When Simulation is not appropriate?
Cont’d
 Not to be performed if the resources or time are not available
 Not advised when no data available.
 If managers have unreasonable expectations or if the power of simulation is over estimated ,
simulation might not be appropriate.
 If the system behavior is too complex or can’t be defined , simulation is not appropriate.
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9. Advantages of simulation
 New policies and all the different rules and regulation of real system can be explored.
 Testing of new systems without committing resources is possible.
 Hypothesis about how or why certain phenomena occur can be tested for feasibility.
 Insight can be obtained about the importance of variables to the performance of the system.
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10. Advantages of simulation cont’d
 Bottleneck analysis can be performed to discover where work in process, information,
Materials and so on are being delayed excessively.
 It can help in understanding how the system operates rather than how individuals think the
system operates.
 “what if” questions can be answered to design the new systems.
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11. Disadvantages of simulation
 Model building requires special training.
 Simulation results can be difficult to interpret.
 Simulation modeling and analysis can be time consuming and expensive.
 Can be used only in some cases when an analytical solution is possible or even preferable.
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12. Areas of Application
 Manufacturing applications
 Wafer fabrication
 Business Process Simulation
 Construction Engineering and Project management
 Logistics, Supply chain and Distribution Applications
 Military applications
 Health Care
 Additional applications
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13. System & Environment
 A system is defined as a group of objects that are joined together in some regular interaction
towards the accomplishment of some purpose
 E.g..: production system manufacturing automobiles
 A system is often affected by changes occurring outside the system, such changes are said to
occur in the system environment.
 In modelling systems, it is necessary to determine the boundary between the system and
environment
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14. Components of system
 Entity: Object of interest in the system.
 Attribute: Property of an entity.
 Activity: Time period of specified length
 State: Collection of variables necessary to describe a system at any time
 Event: An instantaneous occurrence that might change the state of the system.
 Terms such as
 Endogenous: describes the activities and event occur within a system
 Exogenous: describes the activities and events in the environment that affects the system
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15. examples
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16. Types of systems
 Can be classified as discrete and continuous system
 Discrete system is one whose state variables change only at discrete set of points in time
 E. g. : Bank and customers
 No. of customers change only when they arrive or service to be provided has completed.
 Following figure depicts a discrete system
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17. Discrete system state variable
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18. Types of systems
 A continuous system is one in which the state variables change continuously over the time
 E.g. : head of water behind the time
 During excess water, they do flood control, for electricity they draw water
 Following figure depicts continuous system
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19. Continuous system state variable
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20. Model of a system
 A model is defined as a representation of a system for the purpose of studying the system.
 Model is nothing but simplification of the system
 Should be sufficiently detailed to permit valid conclusions to be drawn about the real system
 Different models of the same system could be required as the purpose of investigation
changes.
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21. Types of models
 Models can be mathematical or physical
 A mathematical model uses symbolic notation and mathematical equations to represent a
system
 A physical model is larger or smaller version of an object such as the enlargement of atom or
scaled down version of solar system
 Simulation models can be classified as
 Static or dynamic
 Deterministic or stochastic
 Discrete or continuous
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22.  Static model represents a system at a particular point in time
 Dynamic model  represents the system as they change over time
 Eg: bank simulator from 9 am to 4 pm
 Deterministic model  model that contains no random variables
 Stochastic model  model which has one or more random variables as inputs.
 Random inputs leads to random output
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23. Discrete event system simulation
 State variable changes only at a discrete set of point in time
 The simulation models are analysed by numerical rather than analytical methods
 Analytical methods employ the deductive reasoning of mathematics to solve the model.
 Numerical methods employ computational procedures to solve mathematical models.
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24. Steps in Simulation Study
 Initialization phase (First phase)
1. Problem Formulation
2. Setting objectives and overall project plan
 Model building (Second Phase)
3. Model Conceptualization
4. Data Collection
5. Model Translation
6. Verification
7. Validation
 Third phase
8. Experimental Design
9. Production runs and Analysis
10. More Runs?
 Documentation (Fourth phase)
11. Documentation and Reporting
12. Implementation
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25. 25

26. Problem formulation
 Every study should begin with the statement of the problem
 Problem must be clearly understood by the analyst from those who have the problem
 If the problem statement is still being developed by the analyst, it is important that the policy
makers understand and agree with the formulation.
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27. Setting objectives and overall project plan
 The objectives indicate the questions to be answered by the simulation
 At this point, determination should be made concerning whether simulation is the appropriate
methodology for the problem as formulated and the objectives as stated.
 Should include the plans for the study in terms of the number of people involve, the cost of
study, number of days required to accomplish each phase of the work, along with the results
expected in each stage.
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28. Model conceptualization
 It is not possible to provide a set if instructions that will lead to building successful and
appropriate models in every instance
 Hence it is good to build simple model and build towards greater complexityy
 It is not necessary to have one to one mapping between the model and real system, only
essence of real system is needed.
 Involving the model user will both enhance the quality of the resulting model and increase the
confidence of the model user in the application of the model.
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29. Data collection
 There is direct relation between the construction of model and collection of the needed input
data
 As the model changes the required data elements can also change.
 Data collection takes large portion of time, hence it is necessary to begin as early as possible
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30. Model translation
 Model must be entered into a computer recognizable format
 Model is converted into program to accomplish the desired result with little or no actual
coding
 If the problem is amenable to solution with simulation software, the model development is
greatly reduced.
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31. Verified?
 After converting the model into program, to check whether it performs properly
 With complex models, it is difficult, if not impossible to translate the model successfully in its
entirely without a good deal of debugging
 If the input parameters and logical structure of the model are correctly represented in the
computer, verification is completed.
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32. Validated?
 Achieved through calibration of the model
 An iterative process of comparing the model against the actual system behaviour and using
discrepancies between the two, the insights gained , to improve the model.
 The process is repeated until the accuracy is judged acceptable
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33. Experimental design
 The alternatives that are to be simulated must be determined
 For each system design that is simulated, decisions need to be made concerning the length of
the initialization period, the length of simulation runs and the numbers of replications to be
made of each run.
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34. Production runs and analysis
 Used to estimate measures of performance for the system designs that are being simulated.
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35. More runs?
 After the run is completed, the analyst determines whether additional runs are needed and
what design those additional experiments should follows.
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36. Documentation and reporting
 There are two types of documentation
 Program
 Progress
 Program documentation – here the program is documented well so that if same program when to
be used by another analyst, it can be easily understood hence policymakers and model users can
make decisions based on analysis very easily
 Progress documentation- written history of a simulation project
 Tells about work done and decisions made
 “It is better to work with many intermediate milestones that with one absolute deadline”
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37. implementation
 The success of implementation phase depends on the previous stages
 If the model user has been involved during the entire model building process and if the model
user understands the nature of the model, its outputs, the likelihood of implementation is
enhanced.
 If the model and its underlying assumptions have not been properly communicated, then
implementation will probably suffer, regardless of simulation validity.
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38. exercises
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39. Example 1
 Name the several entities , attributes, events and state variables for the following systems
a) A cafeteria
b) A grocery store
c) A Laundromat
d) A fast food restaurant
e) A hospital emergency room
f) A taxicab company with 10 taxis
g) An automobile assembly line
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40. solution
a) Cafeteria
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Entities Diners (customers)
Attributes 1. Size of appetite (thurst for hunger)
2. Entree preference (choice of main course)
Activities 1. Selecting food
2. Paying for food
Events 1. Arrival at service line
2. Departure from service line
State variables 1. Number of diners in waiting line
2. Number of servers working

41. solution
b) Grocery store
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Entities Shoppers
Attributes 1. Length of grocery list
Activities 1. Checking out
Events 1. Arrival of checkout counters
2. Departure from checkout counter
State variables 1. Number of shoppers in line
2. Numbers of checkout lanes in operation

42. solution
c) Laundromat (coin based- public washing machine)
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Entities Washing machine
Attributes 1. Breakdown rate
Activities 1. Repairing the machine
Events 1. Occurrence of breakdown
2. Completion of service
State variables 1. Number of machine running
2. Number of machine in repair
3. Number of machine in waiting for repair

43. solution
d) Fast food restaurant
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Entities Customers
Attributes 1. Size of order desired
Activities 1. Placing the order
2. Paying the order
Events 1. Arrival at the counter
2. Completion of the purchase
State variables 1. Number of customers waiting
2. Number of position operating

44. solution
e) A hospital emergency room
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Entities Patients
Attributes 1. Attention level required
Activities 1. Providing the service required
Events 1. Arrival of the patients
2. Departure of the patients
State variables 1. Number of patients waiting
2. Number of doctors waiting

45. solution
f) A taxi cab company with 10 taxis
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Entities Fares
Attributes 1. Origination (start location)
2. Destination (end location)
Activities 1. travelling
Events 1. Pick up of fare
2. Drop off of fare
State variables 1. Number of busy taxi cabs
2. Number of fares waiting to be picked up

46. solution
g) Automobile assembly line
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Entities Robot welders
Attributes 1. Speed
2. Breakdown rate
Activities 1. Spot welding
Events 1. Breaking down
State variables 1. Availability of machines

47. Example 2
What are the events and activities associated
with the use of your checkbook?
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48. solution
 Event
 Deposit
 Withdrawal
 Activities
 Writing a check
 Cashing a check
 Making a deposit
 Verifying the account balance
 Reconciling the checkbook with the bank statement
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49. End of unit 1
THANK YOU
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