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Simulations and Modeling

Simulations and Modeling focuses on representing real-world systems using mathematical and computational models. It covers model design, simulation techniques, analysis, and validation, enabling prediction, experimentation, and decision-making in scientific, engineering, and business applications.

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Simulation and Modeling

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Course Title: Simulation and Modeling

Course No: BIT407

Nature of the Course: Theory + Lab

Semester: 7

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 8 + 8

Credit Hours: 3

Course Description

Course Objectives

Course Contents

1. Introduction to Simulation

7 hrs

1.1. System Concept

1.2. System Modeling

1.3. Mathematical Models: Nature and Assumptions

1.4. Verification, Validation, and Calibration of Model

1.5. Model Development Life Cycle

1.6. Advantages and Disadvantages of Simulation

1.7. Limitation of the Simulation Techniques

1.8. Areas of Applications

1.9. Monte Carlo Simulation method

2. Continuous Systems

8 hrs

2.1. Continuous System Model

2.2. Differential Equation

2.3. Analog Method

2.4. Hybrid Computers

2.5. Digital-Analog Simulators

2.6. Continuous System Simulation Languages (CSSLs)

CSMP III

2.7. Hybrid Simulation

2.8. Feedback Systems

3. Discrete System Simulation

9 hrs

3.1. Discrete Events

3.2. Representation of Time

3.3. Generation of Arrival Patterns

3.4. Simulation of a Telephone System

Delay Calls

3.5. Simulation of Programming Tasks

3.6. Gathering Statistics

Counters and Summary Statistics

Measuring Utilization and Occupancy

Recording Distribution and Transit Times

3.7. Discrete Simulation Languages

4. Queuing System

6 hrs

4.1. Characteristics and Structure of Basic Queuing System

4.2. Models of Queuing System

4.3. Queuing Notation

4.4. Single Server and Multiple Server Queuing Systems

4.5. Measurement of Queuing System Performance

4.6. Elementary Idea about Networks of Queuing with Particular Emphasis to Computer System

4.7. Applications of Queuing System

5. Verification and Validation

4 hrs

5.1. Design of Simulation Models

5.2. Verification of Simulation Models

5.3. Calibration and Validation of the models

5.4. Three-Step Approach for Validation of Simulation Models

5.5. Accreditation of Models

6. Analysis of Simulation Output

4 hrs

6.1. Confidence Intervals and Hypothesis Testing

6.2. Estimation Methods

6.3. Simulation Run Statistics

6.4. Replication of Runs

6.5. Elimination of Initial Bias

7. Simulation Languages

7 hrs

7.1. Types of Simulation Languages

7.2. Discrete Systems Modeling and Simulation With GPSS

Resources in GPSS

GPSS Programs

Applications

Structural Data and Control Statements

7.3. Hybrid Simulation

7.4. Feedback Systems: Typical Applications

7.5. SIMSCRIPT Programs

Laboratory Works

1.Simulation of Real Time Systems
2.Queuing Systems Simulation
3.Study of Simulation Tools and Language

Reference Books

1.Jerry Banks, John S. Carson, Barry L. Nelson, David M. Nicole, Discrete Event system simulation, 5th Edition, Pearson Education.
2.Geoffrey Gordon, System Simulation, Prentice Hall of India.
3.A.M Law and W.D. Kelton, Simulation Modeling and Analysis, McGraw Hill.
4.A.M Law and R.F. Perry, Simulation: A Problem-solving approach, Addison Wesley Publishing Company.

Notes:

Source:

This course focuses on introducing modeling and simulation of different types of systems, its validation, verification and analysis of simulation output. It also emphasizes on random number and queuing theory.

To make students understand the concept of simulation and modeling of real time systems.

Practical should include the simulation of some real time systems (continuous and discrete event systems), Queuing Systems, study of Simulation Tools and Language.

This syllabus follows the official BIT curriculum of Tribhuvan University. In case of any doubt or revision, the university’s published syllabus shall be considered authoritative.