Computer Laboratory Manual

Simulation and Modeling

(CS-407)

Computer Science Department

Sir Syed University of Eng. & Technology

University Road, Karachi 75300

Contents

Lab1. Basic Concepts of Simulation and Modeling and SIGMA
(An Introduction).
Lab2. Exploring the Car Wash Model. (Single queue single server)

Lab3. The Car Wash Model (Single Queue two Servers)

Lab4. Implementation of Buffered Queue Model

Lab5. To Design Airport Model. (One queue multiple servers)

Lab6. To Design a superstore model(Two queue and two servers)

Lab7. To Design a Billing System (Two queues one Server)

Lab #1

Basic concepts of Simulation and Modeling

Simulation:

A simulation is an imitation of the operation of real-world process or system over time.

Purpose of Simulation:

  • The behavior of a system is studied by developing a simulation model.
  • New polices, operating procedures, decision rules, information flows and organizational procedures can be explored without disrupting the operation of the real system.

Application Areas of Simulation:

  • Manufacturing Systems
  • Construction System
  • Transportation System
  • Computer System Performance e.t.c.

System:

A collection of entities (people and machines), that interacts together over time to accomplish one or more goals.

System Environment:

A system is affected by the changes occurring outside the system. Such changes are said to occur in the system Environment.

Discrete System:

A discrete system is one in which the state variables change only at a discrete set of points in time.

Continuous System:

A continuous system is one in which the state-variable(s) change continuously over time.

System Model:

An abstract representation of a system, usually containing structural, logical or mathematical relationships that describe a system in terms of state, events, entities and their attributes, events, activities and delays.

System State:

A collection of variables that contain all the information necessary to describe the system at any time

Entity:

Any object or component in the system that requires explicit representation in the model.

for e.g. (a server, a customer, a machine)

Attributes:

The properties of a given entity for e.g. (the priority of a waiting customer.)

Events:

The changes in the state are called events.

OR

An instantaneous occurrence that changes the state of a system

Endogenous Events:

It describes activities and events occurring with in a system. For e.g. (Completion of service of a customer).

Activity:

A duration of time of specified length (a service time) that is known when it begins.

Delay:

A duration of time of unspecified indefinite length, which is not known until it ends.

Introduction to SIGMA

Introduction: I

Sigma Stands for Simulation Graphical Modeling and Analysis .It is a very powerful simulation environment. Sigma is based on the concepts of event graph. Event graph graphically shows the major event taking place in a system and their relationships. Simulation models can be created or edited while they are running. SIGMA simulation model develops and verifies the system in a very short interval of time. SIGMA also provides facility to translate the models into C, English and FORTRAN e.t.c.

Objective:

  • Orientation on Sigma for Windows
  • Exploring Sigma for Windows
  • Translating Models in Sigma for Windows into English, Pascal, C, and various prototype simulation languages.
  • Event Graphs and plot types

GRAPHICAL SIMULATION AND MODELING

Using SIGMA for Windows

Overview

  • SIGMA for Windows is an approach to discrete event simulation modeling:
  • Simulation models can be added, altered or even deleted during a simulation run.
  • We can pause and replay interesting events
  • Includes state of art graphical tracking tools and allows pictures, graphs, plots, and data to be pasted into spreadsheets and word-processors
  • Sigma models can automatically be translated into a variety of languages including C, Pascal, FORTRAN (SIMAN and SLAM prototypes) and English even.
  • Multiple SIGMA sessions can be run concurrently.
  • You can copy and paste objects from one modeling session to another.
  • Supports full simulation model life cycle: from model building and testing to output analysis, animation, documentation, and report writing.

Discrete Event Simulations:

  • Systems in which changes occur at particular instants of time are called discrete event systems. Time is advanced in discrete steps to the next interesting state change.
  • Thereare three elements of Discrete Event System Model.They are:

State-Variables.

Events.

Relationships.

State-Variables:

State-Variables of a system describe completely the state of a system at any time.

For e.g.:

QUEUE: NUMBER OF CARS IN LINE (integer valued)

SERVER: MACHINE IS IDLE/BUSY = 1/0 (integer valued)

The occurrences of activity w.r.t. time changes state-variable’s value.

Events:

The changes in the state are called events.

OR

An instantaneous occurrence that changes the state of a system.

For e.g.:

ENTER, START and LEAVE.

Events are represented by event vertices (nodes or balls) in a SIGMA graph. Event vertex parameters, if any, are given in parentheses.

{QUEUE=QUEUE+1}

File types

  • Model Files .MOD
  • Output Files.OUT
  • Source Code in C .C
  • Source Code in Pascal.PAS
  • Translation in English.ENG
Graphs
Simple Event Graph Edge:
  • Whenever event A occurs, it might cause event B to occur
Conditional Event Graph Edge with a Time Delay:
  • If condition (i) is true at the instant event A occurs, then event B will be scheduled to occur t minutes later

(i)condition

edge

vertex

If the condition is not true, nothing will happen, and the edge can be ignored until the next time event A occurs. You can think of an edge as nonexistent unless its edge condition is true. If the condition for an edge is always true (denoted as 1==1), the condition is left off the graph. We will call edges with conditions that are always true unconditional edges. Zero time delays for edges are not shown on the graph.


(Q) is the vertex parameter, its initial value is provided by the system environment
  • {S=1} system is idol
  • {S=0} system is buzy
  • S>0 means is server idol?
  • Q>0 means are customers waiting?
  • ta is Delay
  • ts is Activity

At the start of the simulation RUN, the first car will ENTER the system. Successive cars ENTER the system everyta minutes. If ENTERing cars find that the server is available (S>0), they can START service. Once cars START service, ts minutes later they can LEAVE. Whenever a car LEAVEs, if the queue is not empty (Q>0), the server will START with the next car.

To run this model, only the starting and ending conditions for the run need to bespecified.

Verbal Event Graphs
  • Before designing your own event graph model, it is a good idea to develop a verbal description of your system.
  • This description will include state changes associated with each vertex along with a verbal description of each edge condition and delay time on the graph.