This book combines clarity of concepts with academic rigours. It adopts a step-by-step approach to learning concepts and solving problems in Operations Research. It is designed to demystify the subject, considered tough by students, and aims at ease of understanding and non-mathematical treatment of the subject.

Preface xv

Chapter 1 Introduction to Operations Research

Definition

Origin and History

Pre-World War II Period (Before 1939)

During World War II (1939-1945)

Post World War II Period (After 1945)

Indian Scenario

Characteristic Features

Need

Scope

Steps

Techniques

Applications

Limitations

Review Questions

Chapter 2 Formulating Linear Programming Problem (LPP)

Linearity

Linear Programming (LP)

Linear Programming Problem (LPP)

Requirements

Assumptions

Applications

Advantages

Limitations

Formulating LP Model – Steps

Review Questions

Self-Practice Problems

Chapter 3 LPP – Optimal Solution by Graphical Method

Steps for Optimal Solution (Two Variable Case)

Review Questions

Self-Practice Problems

Chapter 4 Simplex Method - Simple Problems (For ≤ Type of LPP & for Slack Variable Case)

Steps For Maximization Function

Steps For Minimization Function

Review Questions

Self-Practice Problems

Chapter 5 Simplex Method - Advanced Problems (Optimal Solution Under Big-M Method or Penalty Method)

Big-M Method or Penalty Method

Optimal Solution Under Two-Phase Method

Degeneracy and Cycling Simplex Method

Unbounded Solution Space but Bounded Optimal Solution

Unbounded Solution Space and Unbounded Optimal Solution

Alternative/Multiple Optimal Solutions

Review Questions

Self-Practice Problems

Chapter 6 Duality in Linear Programming

Duality

Constructing Dual LPP

Review Questions

Self-Practice Problems

Chapter 7 Transportation Problem (TP) – Initial Basic Feasible Solution

Transportation Model

Purpose

Constraints

Assumptions

Initial Basic Feasible Solution

Degenerate Solution

Finding IBFS (Initial Basic Feasible Solution) – Steps

Review Questions

Self-Practice Problems

Chapter 8 Transportation Problem – Optimal Solution MODI – Modified Distribution Method

Steps in MODI Method

Transhipment Problem

Formulating Transhipment Problem – Steps

Review Questions

Self-Practice Problems

Chapter 9 Assignment Problem

Features

Assignment Problem Vs Transportation Problem

‘Hungarian Method’ & Optimal Solution

Steps for Obtaining Optimal Solution

Random Method

Restrictions

Travelling Salesman Assignment Problem (TSAP)

Review Questions

Self-Practice Problems

Chapter 10 Game Theory

Game

Game Theory

Types of Games

Basic Assumptions

Finding Value of Game for Pure Strategy – Steps

Finding Value of Game for Mixed Strategy – Steps

For '2 * 2 matrix' or 'Square Matrix'

For 'm * n matrix'

Dominance Property Method

Graphical Method

Pure Strategy

Saddle Point

Pay-Off Matrix

Review Questions

Self-Practice Problems

Chapter 11 Network Analysis

Goals

Applications

Network Diagram

Critical Path Method (CPM)

Critical Path Analysis

Floats

Advantages of CPM

Disadvantages of CPM

PERT

Steps in Finding Critical Path

Optimal Time-Cost Trade-Off Schedule

Project Crashing

Work Breakdown Analysis (WBA)

Review Questions

Self-Practice Problems

Chapter 12 Queuing Theory

Queue

Queuing Theory

Need

Objective

Application

Characteristics

Advantages

Limitations

Queuing Models

Queuing Model I

Queuing Model II

Queuing Model III

Review Questions

Self-Practice Problems

Chapter 13 Replacement Models

Replacement Problems

Factors for Replacement

Replacement Model

Application

Failure and Replacement

Determining Optimum Replacement Age (ORA) or Economic Life

Review Questions

Self-Practice Problems

Chapter 14 Simulation

Meaning

Definition

Examples

Advantages

Limitations

Monte-Carlo Simulation

Solving Problems – Some Computations

Finding Randomized Result – Steps

Review Questions

Self-Practice Problems

Chapter 15 Inventory Models

Meaning of Inventory

Forms of Inventory

Types of Inventory

Need for Inventory

Cost of Inventory

EOQ

Deterministic Inventory Models

Important Computations

Deterministic Inventory Models

Case I – Production/Purchasing Model With No Shortage

Case II – Production Model With Shortages

Probability Inventory Models (Stochastic)

Important Computations

Inventory Models With Price-Breaks

Determining Optimum Order Quantity (OOQ) - Steps

Buffer Stock and Multi-Item Deterministic Inventory Model

Computations

Selective Inventory Control (SIC)

Review Questions

Self-Practice Problems

Chapter 16 Decision Theory

Meaning

Decision Tree Analysis

Assumption

Features

Constructing Decision Tree

Standard Deviation of Probability Distribution of Possible NPVs

Calculation of Co-Efficient of Variation of a Project

Measuring Risk of Project Portfolio

Bayes’ Theorem

Review Questions

Self-Practice Problems

Chapter 17 Investment Decision Analysis

Capital Budgeting

Features / Importance

Difficulties and Problems

Types

Cash Flows

Nature of Cash Flows

Estimating Cash Flows

Capital Budgeting Techniques

Non-Discounted Cash Flow Techniques

Pay-Back Method

Accounting or Average Rate of Return (ARR) Method or Return on Investment (ROI) Method

Surplus Cash Flow Method

Discounted Cash Flow Techniques

NPV (Net Present Value) Method

IRR (Internal Rate Return) Method

PI (Profitability Index) Method

Calculating Present Value of AOCF

Capital Rationing

Methods of Capital Rationing

Capital Budgeting under Risk and Uncertainty

Capital Budgeting under Inflation

Review Questions

Self-Practice Problems

Chapter 18 Statistical Quality Control

Meaning of Quality

Definition of Quality

Quality Control

Benefits of Quality Control

Techniques of Quality Control

Statistical Quality Control (SQC)

Role of SQC

Control Charts

Control Limits

Types of Control charts

Preparing Range Chart

Control Chart for Attributes

Control Chart for Fraction Defective (‘p-chart’)

Control Chart for Number of Defectives also known as ‘np-chart’

Control Chart for Number of Defectives Per Unit (‘C-chart’)

Review Questions

Self-Practice Problems

Chapter 19 Sequencing Problem

Meaning

Assumptions

Determining Optimum Sequence – Johnson Method

Illustrations on Two-Machine Case

Determining Sequencing Time for Three Machines

Converting the ‘three-machine’ Problem into a ‘two-(dummy) machine’ Problem

Illustrations on Three-Machine Case

Determining Sequencing Time for ‘M’ Number of Machines

Converting the ‘m’ Number of Machines Problem into a ‘two-(dummy) machine’ problem

Review Questions

Self-Practice Problems

Appendix

Glossary

Index

Dr. Gurusamy holds a doctorate in Financial Services. He is currently Professor and Head, Department of Commerce, University of Madras, Chennai. He has more than 30 years of teaching and research experience. His area of interest includes accounting and finance, banking and insurance. A prolific writer, he has published books on Financial Services and Systems, Financial Markets and Institutions, Banking Theory Law and Practice and Merchant Banking and Financial Services.