02 20110314-simulation
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This document discusses systems analysis and simulation. It defines a system as a collection of elements that work together to achieve a goal. There are two main types of systems: discrete systems where state variables change at separate points in time, and continuous systems where state variables change continuously over time. A model represents a system in order to study it, as experimenting directly with the real system may not be possible or wise. Simulation models can be static or dynamic, deterministic or stochastic, discrete or continuous. Discrete-event simulation specifically models systems as they progress through time as a series of instantaneous events.
02 20110314-simulation
- 1. Introduction to Simulation and Modeling 4th Undergraduate Level Academic Year 2010/2011, 1 st Term Dr. Mohammed Abdel-Megeed Salem Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Lecture 2 Ain Shams University in Cairo Faculty of Computer and Information Sciences Scientific Computing Department
- 2. Outline Dr. Mohammed Abdel-Megeed Salem Lecture 2 Introduction to Simulation and Modeling
- 3. System Definition “ A collection of elements that function together to achieve a desired goal” – (Blanchard 1991) Key Points: A system consists of multiple elements Elements are interrelated and work in cooperation Exists for the purpose of achieving specific objectives Examples: Traffic Systems Political Systems Economic Systems Manufacturing Systems Service Systems Dr. Mohammed Abdel-Megeed Salem Lecture 1 Introduction to Simulation and Modeling
- 4. System Analysis and Simulation System Real Exp. Exp. with Model Physical Model Mathematical Model Analytical Solution Simulation Dr. Mohammed Abdel-Megeed Salem Lecture 2 Introduction to Simulation and Modeling
- 5. System Analysis and Simulation System Real Exp. Exp. with Model Physical Model Mathematical Model Analytical Solution Simulation Dr. Mohammed Abdel-Megeed Salem Lecture 2 Introduction to Simulation and Modeling
- 6. System Analysis and Simulation Example 1: System: Banking Entities: Customers Attributes: Account balance Activities: Making deposits Events: Arrival and departure State: No# busy tellers, No# waiting customers
- 7. System Analysis and Simulation Example 2: System: Cafeteria Entities: Diners Attributes: Size of appetite Activities: selecting food and paying for food Events: Arrival and departure State: No# diners in waiting line, No# servers working
- 8. System Analysis and Simulation Systems Types: We categorize systems to be of two types, discrete and continuous. A discrete system :is one for which the state variables change instantaneously at separated points in time. A bank is an example of a discrete system (number of customers changes only when customer arrives or departs).
- 9. System Analysis and Simulation Systems Types: We categorize systems to be of two types, discrete and continuous. A continuous system : is one for which the state variables change continuously with respect to time. An airplane moving through the air is an example of a continuous system, since state variables such as position and velocity can change continuously with respect to time.
- 10. System Analysis and Simulation System vs Model It may be impractical to experiment with it. For example, it may not be wise or possible to double the unemployment rate to determine the effect of employment on inflation. A model is a representation of a system for the purpose of studying the system. System Input output Model Input output
- 11. Types of Models Mathematical or Physical A simulation model is a particular type of mathematical model of a system. Simulation Models may be further classified as being Static or Dynamic, Deterministic or Stochastic, Discrete or Continuous.
- 12. System Real Exp. Exp. with Model Physical Model Mathematical Model Analytical Solution Simulation Static Dynamic Deterministic Stochastic Continous Discrete
- 13. System Analysis and Simulation A storehouse with n loading berths There are several 100 trucks daily to serve Loading time of a truck is 50 minutes StorehouseGoal• Cost-effective loading and short waiting timeUsually 2 types• Type 1: Full load with only one product• Type 2: Load consisting of several productsProposals• Fast loading berth for Type 1 customers• Special berth for Type 2 customersProblem• Cannot experiment, changes are expensive!
- 14. Simulation Model Physical Model: useful to build physical models to study engineering systems. Mathematical Model: representing a system in terms of logical and quantitative relationships that are then manipulated and changed to see how the model reacts, and thus how the system would react. Static Simulation Model: is a representation of a system at a particular time. Dynamic Simulation Model: represents a system as it evolves overtime. Deterministic Simulation Model: If a the simulation model does not contain any probabilistic (i.e.,random) components, it is called deterministic
- 15. Simulation Model Stochastic Simulation Models: Having at least some random input components produce output that is itself random, and model therefore be treated as only an estimate of the true characteristics of the model. Continuous vs. Discrete Simulation Models: a discrete simulation model is not always used to model a discrete system and vice versa. Thus a communication channel could be modeled discretely (continuously) if the characteristics and movement of each message (the flow of the messages in aggregate) were deemed important.
- 16. Discrete-Event Simulation Definition of Discrete-Event Simulation Event Barbershop example Dr. Mohammed Abdel-Megeed Salem Lecture 2 Introduction to Simulation and Modeling
- 17. Time Advanced Mechanisms Simulation Clock Next-event time advance Intializied by 0 Advnced to the time of next event Update the state variables Time of next event is updated Continued untill a prespecified stopping condition Fixed-increment time advance
- 18. Example Single Server- single queue (Vodafone shop) problem SOLVED ON WHITE BOARD
- 19. Event Simulation Components System State Simulation Clock Events list Statistical Counters Intialization Routine Timing Routine Event Routine Library Routines Report Generator Main Program
- 20. Contacts Introduction to Simulation and Modeling, 4 th Undergraduate Level, 2009/2010 Dr. Mohammed Abdel-Megeed M. Salem Faculty of Computer and Information Sciences, Ain Shams University Abbassia, Cairo, Egypt Tel.: +2 011 727 1050 Email: mamegeed@hotmail.com http:// cis.shams.edu.eg/Mohammed.Salem/indexEn.html http://www.informatik.hu-berlin.de/~salem