Operations Research: An Introduction

By Christina Pagel
298
2026

Description

Operation Research is a relatively new discipline. The contents and the boundaries of the OR are not yet fixed. Therefore, to give a formal definition of the term Operations Research is a difficult task. The OR starts when mathematical and quantitative techniques are used to substantiate the decision being taken. The main activity of a manager is the decision making. In our daily life we make the decision seven without noticing them. The decisions are taken simply by common sense, judgment and expertise without using any mathematical or any other model in simple situations. But the decision we are concerned here with are complex and heavily responsible. Examples are public transportation network planning in a city having its own layout of factories, residential blocks or finding the appropriate product mix when there exists a large number of products with different profit contributions and production requirement etc. Operations Research tools are not from any one discipline. Operations Research takes tools from different discipline such as mathematics, statistics, economics, psychology, engineering etc. and combines these tools to make a new set of knowledge for decision making. Today, O.R. became a professional discipline which deals with the application of scientific methods for making decision, and especially to the allocation of scarce resources. The main purpose of O.R. is to provide a rational basis for decisions making in the absence of complete information, because the systems composed of human, machine, and procedures may do not have complete information. Operations Research can also be treated as science in the sense it describing, understanding and predicting the systems behaviour, especially man-machine system. This text aims to provide students with a clear, well-structured and comprehensive treatment of the theory and applications of operations research. The methodology used is to first introduce the students to the fundamental concepts through numerical illustrations and then explain the underlying theory, wherever required. Inclusion of case studies in the existing chapters makes learning easier and more effective. The book introduces the readers to various models of Operations Research (OR), such as transportation model, assignment model, inventory models, queueing theory and integer programming models. Various techniques to solve OR problems' faced by managers are also discussed. Operations Research provides a broad focus on algorithmic and practical implementation of Operations Research (OR) techniques, using theory, applications, and computations to teach students OR basics. The book can be used conveniently in a survey course that encompasses all the major tools of operations research, or in two separate courses on deterministic and probabilistic decision-making.

About Author

Christina Pagel is a German-British mathematician and professor of operational research at University College London (UCL) within UCL's Clinical Operational Research Unit (CORU), which applies operational research, data analysis and mathematical modelling to topics in healthcare. She was Director of UCL CORU from 2017 to 2022 and is currently Vice President of the UK Operational Research Society. She also co-leads, alongside Rebecca Shipley, UCL's CHIMERA research hub which analyses data from critically ill hospital patients. She received a Ph.D. in Space Physics from Imperial College London, an M.Sc. in mathematical physics from King's College London, an M.Sc. in applied statistics from University of London, a Bachelors Degree in mathematics from University of Oxford, and two M.A. degrees in Medieval History and Classical Civilization from the University of London.

Table of Content

Preface
Chapter 1. Introduction to Operations Research

Definition and Scope of Operations Research
History and Evolution of OR
Characteristics of OR
Phases of Clinical Research
Applications of OR in Different Fields

Chapter 2. Linear Programming – Formulation and Graphical Method
Introduction to Linear Programming
Structure of a Linear Programming Problem
Assumptions and Properties of LPP
Formulation of LPP Models
Graphical Solution Method

Chapter 3. Linear Programming – Simplex Method
Basic Feasible Solutions
Simplex Algorithm: Basic Concepts
Computational Procedure of Simplex Method
Artificial Variables: Big M Method

Chapter 4. Duality in Linear Programming
Concept of Duality
Formulation of the Dual Problem
Duality Theorems
Primal-Dual Relationships
Economic Interpretation of Dual

Chapter 5. Transportation Problem
Introduction to Transportation Problems
Mathematical Formulation
Initial Basic Feasible Solution
(North-West Corner, LCM, VAM)
Optimality Test (MODI and Stepping Stone Method)
Degeneracy in Transportation
Chapter 6. Assignment Problem
Assignment Model Overview
Hungarian Method for Assignment
Optimality in Assignment Problems
Unbalanced Assignment Problems
Traveling Salesman Problem

Chapter 7. Game Theory
Introduction to Game Theory
Two-Person Zero-Sum Games
Pure Strategy Games and Saddle Point
Mixed Strategies
Dominance Rule

Chapter 8. Decision Theory
Introduction to Decision Theory
Types of Decision-Making Environments
Decision Making Under Certainty
Decision Making Under Risk
Decision Making Under Uncertainty
Expected Utility Hypothesis

Chapter 9. Queuing Theory
Basic Concepts and Terminology
Queueing Networks
Characteristics (Kendall’s Notation)
M/M/1 Queue Model
M/M/c and M/G/1 Queues

Chapter 10. Inventory Management
Inventory and Its Types
Costs Associated with Inventory
Economic Order Quantity (EOQ) Model
Reorder Level and Safety Stock
ABC Analysis

Bibliography
Index