IOE Syllabus – Operations Research / Management Science

Course Objectives:

5.

Risk Analysis

(10 hours)

To make capable of managing data, analyzing data such as sorting, pivoting tables,

5.1. Monte Carlo Simulation

5.2. Applications of Monte Carlo Simulation

and applying statistical analysis in a spreadsheet environment. To familiarize with

5.3. Building Monte Carlo Simulation Models

forecasting methods, linear programming, inventory models. To make familiar with

5.4. Different Probability Distributions

simulation in

decision-making under risk and uncertainty with

the use

of risk

5.5. Building Simulation Models with CRYSTAL BALL & analysis

analysis software such as CRYSTAL BALL. To make capable in applying the

knowledge gained during the course for solving real problems in decision-making.

6.

Optimization and Simulation

(4 hours)

6.1. Optimization under uncertainty

1.

Introduction to Modeling for Decisions & Data Management and

Analysis

(7

6.2. Optimization and Monte carlo simulation

6.3. Use of OPTQUEST and CRYSTAL BALL

hours)

1.1. application and benefits of Operations Research

1.2. developing Models

1.3. analyzing and solving models; interpretation and Use of Model Results

1.4. applications of Data Management and Analysis

Practical:

1.5. data Storage and Retrieval & data Visualization

Course project on real and practical problems such as forecasting, queuing, inventory and

2. Regression Analysis & Time series analysis

(10 hours)

optimization problems has to be done. The report has to be submitted on the acceptable

2.1. Regression Analysis

format at the end of the course. Group presentation should be carried out at the end of the

2.1.1. Simple linear regression

course period.

2.1.2. Multiple linear regression

2.2. Forecasting models with

2.2.1. trend components

References:

2.2.2. seasonal components

2.2.3. trend and seasonal components

1.

Ragsdale, Cliff T., “Spreadsheet Modeling and Decision Analysis, A Practical

2.2.4. Selecting the best forecasting methods

Introduction to Management Science”, South Western, Cengage Learning.

2.2.5.

Forecasting with CB predictor

2.

Wayne Winston, and S. Christian Albright, “Practical Management Science:

3.

Introduction to optimization

(10 hours)

Spreadsheet modeling and applications”, Thompson Learning.

3.

Camm, Jeffrey D. and James R. Evans, “Management Science & Decision Technology”,

3.1. Modeling optimization problem in EXCEL

South – Western College Publishing, A Division of Thompson Learning, USA.

3.2. Building Linear Programming Models

4.

Hillier, Frederick S., Mark S. Hillier, and Gerald

J. Lieberman, “Introduction to

3.3. Solving Linear Programming Models

Management Science: A Modeling and Case Studies Approach with Spreadsheets”,

3.4. Network modeling

McGraw-Hill International Editions.