Review on Energy Resilience
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Capter01WhatisSimulation20slidesin50minutes.pptxSystem Simulation Modeling and Analysis
Chapter 1 – What Is Simulation?
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ISE 4383/5383
Chapter 1 – What Is Simulation?
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System Study
Chapter 1 – What Is Simulation?
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Work With the System?
Study the system – measure, improve, design, control
Maybe just play with the actual system
Advantage — unquestionably looking at the right thing
But it’s often impossible to do so in reality with the actual system
System doesn’t exist
Would be disruptive, expensive, or dangerous
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Chapter 1 – What Is Simulation?
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Ways to Study a System
System
Experiment with the Actual System
Experiment with a Model of the System
Physical Model
Mathematical Model
Analytical Solution
Simulation
Experiment with the Actual System
Physical Model
Analytical Solution
Obtained from: Law, A.M. 2007, Simulation Modeling and Analysis, 3rd ed., McGraw-Hill, New York, NY.
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Chapter 1 – What Is Simulation?
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Models
Model – set of assumptions/approximations about how the system works
Study the model instead of the real system … usually much easier, faster, cheaper, safer
Can try wide-ranging ideas with the model
Make your mistakes on the computer where they don’t count, rather than for real where they do count
Often, just building the model is instructive – regardless of results
Model validity (any kind of model … not just simulation)
Care in building to mimic reality faithfully
Level of detail
Get same conclusions from the model as you would from system
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Chapter 1 – What Is Simulation?
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Types of Models
Physical (iconic) models
Tabletop material-handling models
Spaghetti structures
Flight simulators
Logical (mathematical) models
Approximations and assumptions about a system’s operation
Often represented via computer program in appropriate software
Exercise the program to try things, get results, learn about model behavior
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Chapter 1 – What Is Simulation?
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Studying Logical Models
If model is simple enough, use traditional mathematical analysis … get exact results, lots of insight into model
Queueing theory
Differential equations
Linear programming
But complex systems can seldom be validly represented by a simple analytic model
Danger of over-simplifying assumptions … model validity?
working on the wrong problem
Often, a complex system requires a complex model, and analytical methods don’t apply … what to do?
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System Complexity
System complexity is a function of two factors:
1. Interdependencies
2. Variability
(Interdependencies + Variability = Complexity)
Chapter 1 – What Is Simulation?
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Chapter 1 – What Is Simulation?
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Chapter 1
What is Simulation?
Last revision January 22, 2007
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Chapter 1 – What Is Simulation?
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Simulation Is …
Simulation – very broad term – methods and applications to imitate or mimic real systems, usually via computer
Applies in many fields and industries
Very popular and powerful method
_ This chapter – general ideas, terminology, examples of applications, good/bad things, kinds of simulation, software options, how/when simulation is used
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Chapter 1 – What Is Simulation?
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Systems
System – facility or process, actual or planned
Examples abound …
Manufacturing facility
Bank operation
Airport operations (passengers, security, planes, crews, baggage)
Transportation/logistics/distribution operation
Hospital facilities (emergency room, operating room, admissions)
Computer network
Freeway system
Business process (insurance office)
Criminal justice system
Chemical plant
Fast-food restaurant
Supermarket
Theme park
Emergency-response system
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Chapter 1 – What Is Simulation?
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Computer Simulation
Broadly interpreted, computer simulation refers to methods for studying a wide variety of models of systems
Numerically evaluate on a computer
Use software to imitate the system’s operations and characteristics, often over time
Can be used to study simple models but should not use it if an analytical solution is available
Real power of simulation is in studying complex models
Simulation can tolerate complex models since we don’t even aspire to an analytical solution
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Chapter 1 – What Is Simulation?
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Popularity of Simulation
Has been consistently ranked as the most useful, popular tool in the broader area of operations research / management science
Hardware and software have improved, probably making simulation even more attractive
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Chapter 1 – What Is Simulation?
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Popularity of Simulation (cont’d.)
www.wintersim.org
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Chapter 1 – What Is Simulation?
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Advantages of Simulation
Flexibility to model things as they are (even if complicated)
Avoid looking where the light is (a morality play):
Allows uncertainty, nonstationarity in modeling
The only thing that’s for sure: nothing is for sure
Danger of ignoring system variability
Model validity
You’re walking along in the dark and see someone on hands and knees searching the ground under a street light.
You: “What’s wrong? Can I help you?”
Other person: “I dropped my car keys and can’t find them.”
You: “Oh, so you dropped them around here, huh?”
Other person: “No, I dropped them over there.” (Points into the darkness.)
You: “Then why are you looking here?”
Other person: “Because this is where the light is.”
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Chapter 1 – What Is Simulation?
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Advantages of Simulation (cont’d.)
Advances in computing/cost ratios
Estimated that 75% of computing power is used for various kinds of simulations
Advances in simulation software
Far easier to use (GUIs)
No longer as restrictive in modeling constructs (hierarchical, down to C)
Statistical design & analysis capabilities
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Chapter 1 – What Is Simulation?
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The Bad News
Don’t get exact answers, only approximations, estimates
Also true of many other modern methods
Get random output (RIRO) from stochastic simulations
Statistical design, analysis of simulation experiments
Exploit: noise control, replicability, sequential sampling, variance-reduction techniques
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Overview of a Simulation Study
Understand the system
Be clear about the goals
Develop a conceptual model
Translate into modeling software
Verification
Validation
Design experiments
Make runs
Analyze, get insight, document results
Chapter 1 – What Is Simulation?
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Chapter 1 – What Is Simulation?
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Model Taxonomy
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Chapter 1 – What Is Simulation?
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Different Kinds of Simulation
Static vs. Dynamic
Does time have a role in the model?
Continuous-change vs. Discrete-change
Can the “state” change continuously or only at discrete points in time?
Deterministic vs. Stochastic
Is everything for sure or is there uncertainty?
Most operational models:
Dynamic, Discrete-change, Stochastic
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Chapter 1 – What Is Simulation?
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Dimensions for Classifying Simulation Models
Discrete
Continuous
Dynamic
Static
State Variables
Time Dependence
Model Inputs
Deterministic
Stochastic
Our Focus: Discrete Event Simulation
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Chapter 1 – What Is Simulation?
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Discrete Event Simulation (DES)
Modeling of a system as it evolves over time in which the system state change instantaneously at separate points in time at which an event occurs
The system can change at only a countable number of points in time
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Chapter 1 – What Is Simulation?
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Discrete Event Simulation Key Terms
System State: Collection of variables necessary to describe a system at a particular time, relative to the objectives of a study
Simulation Event: an instantaneous occurrence that may change the System State
Arrival
Departure
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Chapter 1 – What Is Simulation?
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Example: Automobile Supply Chain
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Chapter 1 – What Is Simulation?
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Sources of Complexity?
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Chapter 1 – What Is Simulation?
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Using Computers to Simulate
General-purpose languages (FORTRAN, C, C++, C#, Java, Matlab, others)
Tedious, low-level, error-prone
But, almost complete flexibility
Support packages
Subroutines for list processing, bookkeeping, time advance
Widely distributed, widely modified
Spreadsheets
Usually static models
Financial scenarios, distribution sampling, SQC
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Chapter 1 – What Is Simulation?
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Using Computers to Simulate (cont’d.)
Simulation languages
GPSS, SLX, SIMAN (on which Arena is based, and is included in Arena)
Popular, some are still in use
Learning curve for features, effective use, syntax
High-level simulators
Very easy, graphical interface
Domain-restricted (manufacturing, communications)
Limited flexibility — model validity?
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Chapter 1 – What Is Simulation?
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Where Arena Fits In
Hierarchical structure
Multiple levels of modeling
Can mix different modeling levels together in the same model
Often, start high then go lower as needed
Get ease-of-use advantage of simulators without sacrificing modeling flexibility
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Chapter 1 – What Is Simulation?
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When Simulations are Used
Uses of simulation have evolved with hardware, software
The early years (1950s-1960s)
Very expensive, specialized tool to use
Required big computers, special training
Mostly in FORTRAN (or even Assembler)
Processing cost as high as $1000/hour for a sub-286 level machine
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Chapter 1 – What Is Simulation?
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When Simulations are Used (cont’d.)
The formative years (1970s-early 1980s)
Computers got faster, cheaper
Value of simulation more widely recognized
Simulation software improved, but they were still languages to be learned, typed, batch processed
Often used to clean up “disasters” in auto, aerospace industries
Car plant; heavy demand for certain model
Line underperforming
Simulated, problem identified
But demand had dried up — simulation was too late
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Chapter 1 – What Is Simulation?
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When Simulations are Used (cont’d.)
The recent past (late 1980s-1990s)
Microcomputer power
Software expanded into GUIs, animation
Wider acceptance across more areas
Traditional manufacturing applications
Services
Health care
“Business processes”
Still mostly in large firms
Often a simulation is part of the “specs”
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Chapter 1 – What Is Simulation?
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When Simulations are Used (cont’d.)
The present
Proliferating into smaller firms
Becoming a standard tool
Being used earlier in design phase
Real-time control
The future
Exploiting interoperability of operating systems
Specialized “templates” for industries, firms
Automated statistical design, analysis
Networked sharing of data in real time
Integration with other applications
Distributed model building, execution
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Chapter 1 – What Is Simulation?
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When Simulation Is the Appropriate Tool
Simulation is one of the most widely used and accepted tools in OR and systems analysis due to:
Availability of special-purpose simulation languages
Massive computing capabilities at a decreasing cost per operation
Advances in simulation methodologies
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Chapter 1 – What Is Simulation?
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When Simulation Is the Appropriate Tool (cont’d)
…execute informational, organizational, and environmental changes, and allow the effect of these alterations on the model’s behavior to be observed.
…can afford valuable insight as to which system variables are most important and how variables interact by changing simulation model inputs and observing the resulting output.
…enable the study of, and experimentation with, the internal interactions of a complex system, or of a subsystem within a complex.
…assist in suggesting improvement in the system under investigation through using knowledge gained from the process of designing and constructing of a simulation model.
Simulation models can…
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Chapter 1 – What Is Simulation?
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When Simulation Is the Appropriate Tool (cont’d)
…can determine process and resource requirements by simulating different capabilities for a system.
…provide animation that shows a system in simulated operation so that the proposed plan can be visualized.
…be used to experiment with new designs or policies prior to implementation, so as to prepare for what may happen.
…be designed for employee training to allow learning without the cost and disruption of actual on-the-job learning.
Simulation models can…
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 1: Do not use simulation when the problem can be solved using common sense
Example:
Mean Arrival Rate (): 100 arrivals/hour
i.e., Mean Interarrival Time: 0.01 hours, or 0.6 minutes
Mean Service Rate (): 12 customers/hour
i.e., Mean Service Time: 0.08 hours, or 5 minutes
What is the minimum number of servers needed?
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 2: Do not use simulation when the problem can be solved analytically
For example, under steady-state conditions, basic operating characteristics in the previous example can easily be determined using principles from Queueing Theory. (Refer to “Chapter 17: Queueing Theory” in Introduction to Operations Research by F.S. Hillier and G.J. Lieberman, 2001)
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 3: Do not use simulation when its easier to perform direct experiments
What is the effect of…
using a hand-held cash register and headset vs. adding an additional order placement station?
Example:
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 4: Do not use simulation when the costs exceed the savings
There are many steps in completing a simulation study and these must be done THOROUGHLY.
If it costs $20,000 to perform a simulation study and the savings might be at most $10,000, then simulation would not be appropriate.
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 5: Do not use simulation if the resources are not available
RULE 6: Do not use simulation if time is not available
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 7: Do not use simulation if the appropriate data is not available
RULE 8: Do not use simulation if verifying and validating the model will be difficult, if not impossible
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Chapter 1 – What Is Simulation?
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When Simulation Is NOT the Appropriate Tool (cont’d)
Obtained from: Banks, J. and Gibson, R.R., 1997, “Don’t Simulate When: 10 Rules for Determining When Simulation Is Not Appropriate,” IIE Solutions, September.
RULE 9: Do not use simulation if expectations are unreasonable
RULE 10: Do not use simulation if the system behavior is too complex or cannot be defined
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