Operation Research: Concepts, Techniques and Applications
Master Operations Research Through Concepts, Techniques, and Practical Problem-Solving
Learn Linear Programming, Simplex Methods, Transportation, Assignment, TSP, Network Analysis, CPM, PERT, Queuing Theory, Game Theory, and Sequencing through structured explanations, numerical examples, and step-by-step problem-solving techniques.
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About
About the Book
Operations Research: Concepts, Techniques, and Applications is a structured and practical guide to understanding the principles, techniques, and applications of Operations Research (OR). The book is designed to help students and learners develop the analytical and mathematical skills required to model problems, evaluate alternatives, optimize resources, and make informed decisions.
Beginning with the fundamentals of Operations Research, the book introduces the evolution, scope, characteristics, applications, models, and phases of an OR study. It then progressively moves into important optimization techniques, including Linear Programming, the Simplex Method, advanced LPP techniques, Transportation Problems, Assignment Problems, and the Travelling Salesman Problem.
The book also covers important project and decision-making techniques such as Network Analysis, CPM, PERT, project crashing, Queuing Theory, Game Theory, and Sequencing Problems.
A major focus of the book is its step-by-step problem-solving approach. Mathematical and analytical concepts are presented in a structured manner so that readers can understand not only the theory behind a technique but also how it can be applied to solve practical problems.
Topics such as the Graphical Method, Big-M Method, Two-Phase Simplex Method, Duality, MODI Method, Vogel’s Approximation Method, Hungarian Method, Little’s Method, Fulkerson’s Rule, CPM, PERT, M/M/1 and M/M/C queuing models, dominance principle, mixed strategies, and Johnson’s Algorithm are presented as part of the learning journey.
The book connects Operations Research techniques with practical situations in business, manufacturing, logistics, transportation, supply chain management, project planning, scheduling, service systems, engineering, and management.
Key Features- Systematic coverage of major Operations Research concepts
- Step-by-step explanation of mathematical techniques
- Solved numerical problems and practical examples
- Linear Programming and Simplex-based methods
- Transportation and Assignment Problems
- Travelling Salesman Problem
- Network Analysis and project scheduling
- CPM and PERT techniques
- Queuing models and waiting-line analysis
- Game Theory and decision-making
- Sequencing problems and scheduling algorithms
- Applications of OR in real-world decision-making
- Student-friendly explanations and structured learning
The book is particularly suitable for BCA, BTech, MCA, MBA, MSc Mathematics, MSc Statistics, Engineering, and Management students, as well as educators, researchers, business analysts, and professionals who want to develop a practical understanding of Operations Research.
Whether you are studying OR as part of an academic course, preparing for examinations, strengthening your numerical problem-solving skills, or exploring optimization techniques for practical applications, this book provides a structured foundation for learning and applying Operations Research.
Author
About the Author
Anshuman Kumar Mishra, M.Tech (Computer Science) Assistant Professor, Doranda College, Ranchi University
Prolific Author of 50+ Books on AI, Machine Learning & Computer Science | 20+ Years Experience
Anshuman Kumar Mishra is a dedicated educator, researcher, and highly prolific author with over 20 years of experience in Computer Science and Information Technology. Holding an M.Tech in Computer Science from BIT Mesra, he brings a rare combination of academic depth and practical teaching expertise.
Currently serving as Assistant Professor at Doranda College under Ranchi University, he has mentored thousands of students, helping them build strong foundations in programming, data science, and artificial intelligence. His student-centric teaching style emphasizes conceptual clarity, hands-on practice, and real-world application.
Anshuman is a prolific author with more than 50 books published across a wide spectrum of computer science and emerging technology domains. From foundational programming languages to advanced topics in Artificial Intelligence, Machine Learning, Reinforcement Learning, Decision Theory, and Computer Vision — his books are widely appreciated by students, educators, and professionals for their clear explanations, strong theoretical foundation, and practical approach.
His extensive body of work reflects his deep commitment to making complex subjects accessible and meaningful for learners at all levels. He is particularly recognized for creating well-structured learning paths that help readers progress from beginner to advanced levels with confidence.
Driven by the mission to democratize quality technical education, Anshuman continues to write and update books that bridge the gap between academic theory and industry practice.
When not teaching or writing, he actively follows and explores new developments in AI, Quantum Machine Learning, and Ethical Intelligence systems.
Contents
Table of Contents
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