Description
Operations Research is an analytical tool used to supplement managers in decision-making which is an important function of the management of any organization. This book deals with the application of quantitative techniques in Operations Research through a large number of examples which would aid students in understanding the optimization techniques in depth and managers in tackling different problems associated with decision-making such as determination of optimum quantity of products to be manufactured, quantity of products to be transported, assignment of work, selection of strategy and determination of optimum time.
Table of Content
Chapter 1 INTRODUCTION
1.1 Origin and Development of Operations Research
1.2 Definition of OR
1.3 Areas of Application of OR
1.4 OR Methodology
1.5 Features and Limitations of OR
Chapter 2 LINEAR PROGRAMMING
2.1 Introduction
2.2 Formulation of Linear Programming Models
2.3 Graphical Solution of Linear Programming Problem (LPP)
Exercises
Chapter 3 SIMPLEX METHOD
3.1 Introduction
3.2 Slack and Surplus Variables
3.3 Basic Solution
3.4 Basic Feasible Solution
3.5 Optimum Basic Feasible Solution
3.6 Simplex Problem in Table Form
3.7 Minimisation Problem
3.8 Artificial Variable
3.9 Two-phase Method
3.10 Degeneracy in LPP
Exercises
Chapter 4 DUAL SIMPLEX METHOD
4.1 The Dual Problem
4.2 General Primal–Dual Pair
4.3 Formulation of a Dual Problem
4.4 Economic Interpretation of Dual Problem
4.5 Dual Simplex Method
Exercises
Chapter 5 TRANSPORTATION PROBLEMS
5.1 Introduction
5.2 Formulation of LPP
5.3 Methods of Obtaining Initial Basic Feasible Solution
5.4 Optimality Check
5.5 Balanced Transportation Problem
5.6 Degeneracy in Transportation Problem
5.7 Maximisation Problems
Exercises
Chapter 6 ASSIGNMENT PROBLEMS
6.1 Introduction
6.2 Hungarian Method
6.3 Ticking Method
6.4 Maximisation Problem
6.5 Travelling Salesman Problems
Exercises
Chapter 7 GAME THEORY
7.1 Introduction
7.2 Two-person Zero-sum Game
7.3 Pay-off Matrix
7.4 The Maximin and Minimax Principle
7.5 Saddle Point
7.6 Theory of Dominance
7.6.1 General Rule for Dominance
7.7 Mixed Strategy Game with 2×2 Pay-off Matrix and without Saddle Point
7.8 Graphical Solution
Exercises
Chapter 8 NETWORK ANALYSIS
8.1 Introduction
8.2 Basic Rules for Drawing Networks
8.3 Types of Activities
8.4 Fulkerson’s Rule
8.5 Critical Path in Network Analysis
8.6 Scheduling of Activities
8.7 Performance Evaluation and Review Technique (PERT)
8.8 Critical Path Method (CPM)
Exercises
Chapter 9 QUEUING THEORY
9.1 Introduction
9.2 Characteristics of Queuing System
9.3 Pure Birth Model
9.4 Pure Death Model
9.5 Steady-state Performance Analysis
9.6 Single-server Queuing Models
9.7 Multiple Server Models
Exercises
Chapter 10 REPLACEMENT PROBLEM
10.1 Introduction
10.2 Replacement of Items Whose Maintenance Cost Increases with Time and
Value of Money Remains Same During the Period
10.3 Replacement of Items Whose Maintenance Cost Increases with Time and
Value of Money also Changes with Time
10.4 Present Value Concept
10.5 Replacement of Items that Fail Completely
10.5.1 Individual Replacement Policy
10.5.2 Group Replacement Policy
10.6 Rate of Replacement and Total Cost in Group Replacement
10.7 Staff Problem
Exercises
Chapter 11 DYNAMIC PROGRAMMING
11.1 Introduction
11.2 Dynamic Programming System
11.3 Dynamic Programming for Profit Optimisation
Chapter 12 SEQUENCING
12.1 Introduction
12.2 Assumptions
12.3 n Jobs and 2 Machines
12.3.1 Algorithm
12.4 n Jobs and 3 Machines in the Order ABC
12.5 Two Jobs and n Machines
Exercises
Chapter 13 INTEGER PROGRAMMING PROBLEMS
13.1 Introduction
13.2 Gomory’s Constraint
13.3 Pure and Mixed Integer Programming Problems
13.4 Zero–one Programming Problem
13.5 Gomory’s All-integer Cutting Plane Method
13.6 Geometrical Interpretation of the Cutting Plane Method
13.7 Branch and Bound Method
Exercises
Chapter 14 DECISION ANALYSIS
14.1 Introduction
14.2 History of Decision Analysis
14.3 A Prototype Example
14.4 Decision-making without Experimentation
14.4.1 Maximin Principle
14.4.2 Most Likely Principle
14.4.3 Bayes’ Decision Rule
14.4.4 Sensitivity Analysis
14.5 Decision-making with Experimentation
14.5.1 A Prototype Example 1
14.5.2 A Prototype Example 2
14.6 The General Decision Tree Model
Exercises
Chapter 15 METAHEURISTICS
15.1 Introduction
15.2 Nature of Metaheuristics
15.3 A Travelling Salesman Problem
15.4 Tabu Search
15.4.1 Steps in Tabu Search Method
15.5 Spanning Tree
15.6 Simulated Annealing
Chapter 16 SIMULATION
16.1 Introduction
16.2 Simulation Process
16.3 Types of Simulation
16.3.1 Total Enterprise Simulation
16.3.2 Interactive Simulation
16.3.3 Non-interactive Simulation
16.3.4 Functional Simulation
16.3.5 Concepts Simulation
16.3.6 Planning Simulation
16.3.7 Process simulation
16.4 The Basic Steps in Simulation
16.5 When to use Simulation?
16.5.1 Type of Problem
16.5.2 Availability of Resources
16.5.3 Costs
16.5.4 Availability of Data
16.6 Monte Carlo Simulation
16.6.1 Steps in Monte Carlo Simulation
16.8 Advantages and Disadvantages of Simulation
16.8.1 Advantages
16.8.2 Disadvantages
Exercises
Chapter 17 PROJECT MANAGEMENT
17.1 Introduction
17.2 Phases of Project Management
17.2.1 Planning
17.2.2 Scheduling
17.2.3 Controlling
17.3 Work Breakdown Structure
17.4 Control Charts
17.5 Control Charts for Variables
17.5.1 Objectives of Control Charts for Variables
17.5.2 X-Chart and R-Chart
17.5 Limitations of Variable Charts
17.6 Control Charts for Attributes
17.7 P-Chart
17.7.1 Comparison of X- and R-Chart with P-Chart
17.7.2 Limitations of P-Chart
17.8 nP-Charts
17.9 Difference between Defect and Defective
17.9.1 Types of Defects
17.10 Control Charts for Defects
17.11 Control Charts for Defects Per Unit
• Exercises
• Appendix
• Bibliography
• Index
About The Author
B.J. Ranganath is a distinguished professor with 45 years of teaching and research experience. He has authored books on Tool Engineering and Manufacturing Engineering, and has guided 12 Ph.D. students. He has published 250 technical papers in journals and conferences.
New Product Tab
Here's your new product tab.
Reviews
There are no reviews yet.