# 4470lec1 - COIS4470H/AMOD5810H Modelling and Simulation...

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1 COIS4470H/AMOD5810H Modelling and Simulation Winter 2010 Instructor: Dr. Wenying Feng

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2 Course Description This course provides an introduction to computational and mathematical techniques for modeling, simulation, and analyzing the performance of various systems by using simulation. Stochastic, dynamic and discrete- event systems models are studied.
3 Goals • We will study: how systems operate and respond to change by modeling, simulate, and analyze simple-but- representative systems. • We will use: computer programs and mathematical analysis. • Prerequisite: programming with at least one language Recommended: a course in statistics

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4 Text L. M. Leemis and S. K. Park: Discrete-Event Simulation, a first course Prentice Hall, 2006. Lecture Notes will be posted on the WebCT T. J. Schriber (reference): An introduction to simulation usin GPSS/H, John Wiley & Sons, 1991.
5 Topics • Introduction • The Single Server Service Node • A Simple Inventory System • Random Number Generation • Discrete-Event Simulation • Next-Event Simulation • Simulation Languages – GPSS • Statistics and Random Variables • Output Analysis • Introduction to Queueing Models

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6 Grading • 35% Assignments and in class exercises • 10% Presentation • 20% midterm test • 35% Final examination
7 What is a Model? o An abstraction of a system (a collection of interacting elements or components that act together to achieve a common goal) o Usually takes the form of a set of assumptions concerning the operation of the system o Models are used to: - analyze behavior of certain components - investigate various changes to system components - predict future enhancements o In short, models provide a laboratory environment in which to study a system even before it exists or without affecting the current implementation. o Models can be evaluated using simulation or analytical means

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8 Reasons for experimenting with a model o The system may only be in planning stage o System performance under new workload can be evaluated more efficiently o System performance under new configuration can be evaluated more efficiently o Can get result faster o Generally cost less o Model is less risky to experiment with
9 Ways to Study a System Ways to Study a System

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10 Simulation Modelling Simulate : perform experiments using computer implementation of the model • Can model and study systems of arbitrary complexity • Often costly to develop and run the simulation programs • Generally not easy to give interpretations to the relationships between input parameters and performance measures
11 Analytic Modelling Analytic Modelling : solve by mathematical methods • Usually less costly to compute numerical results • Easier to give interpretation to results • Solutions to complex models are not available

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Advantages of Simulation • Ability to compress time, expand time • Ability to control sources of variation • Avoids errors in measurement • Ability to stop and review
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## This note was uploaded on 02/14/2010 for the course COMPUTER S COIS-3030 taught by Professor Hircock during the Spring '10 term at Trent University.

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4470lec1 - COIS4470H/AMOD5810H Modelling and Simulation...

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