Operations research / Mansi Bhatnagar.

Includes bibliographical references and index.

1: Introduction of operation research -- 1.1. Definition of OR -- 1.2. History of OR -- 1.3. Evolution of operation research -- 1.4. Management science -- 1.5. Techniques of OR used in management science -- 1.6. Journals of OR -- 1.7. Features/characteristics of OR -- 1.8. Phases or methodology of operation research study -- 1.9. Scope and application of operations research (OR) -- 1.10. Application of various operation research techniques -- 1.11. Role of computers in operation research -- 1.12. Advantages of operation research -- 1.13. Limitations of operations research (OR) -- 1.14. Summary -- 2: Operations research and optimization techniques -- 2.1 Operations research (OR) mechanism -- 2.2 Operations research (OR): the approach -- 2.3 General mathematical models -- 2.4 Optimization techniques using mathematical programming -- 2.5 Linear programming (LP) an introduction -- 2.6 Applications of linear programming (LP) in program management -- 2.7 Summary -- 3: Operations research and managerial decision making -- 3.1 Origin, history, and developments -- 3.2 Operations Research (OR) and decision making -- 3.3 The sequence of OR in decision making -- 3.4 Advantages of operation research in effective decisions making -- 3.5 Areas of application -- 3.6 Techniques -- 3.7 Model -- 3.8 Computer in OR and decision making -- 3.9 Summary -- 4: Overview of the operations research modeling approach -- 4.1 Defining the problem and gathering data -- 4.2 Formulating a mathematical method -- 4.3 Deriving solutions from the model -- 4.4 Testing the model -- 4.5 Preparing to apply the model -- 4.6 Implementation -- 4.7 Summary -- 5: Implementation and evaluation of OR solutions -- 5.1 Implementation of OR solutions -- 5.2 The evaluation of operations research (OR) solutions -- 5.3 Limitation in implementation an evaluation of OR -- 5.4 An example of implementation and evaluation of OR solution -- 5.5 Summary -- 6: Challenges to operations research -- 6.1 Operations research (OR) as study and practice -- 6.2 Operations researchers as generalists -- 6.3 Challenges of operations research -- 6.4 Challenges of OR in academia -- 6.5 Sustainability and operations research (OR) challenges -- 6.6 Future operations research (OR) challenges or researchers -- 6.7 Summary -- 7: Real-world applications of operations research -- 7.1 Production planning at Harris Corporation -- 7.2 Gasoline blending at Texaco -- 7.3 FMS scheduling at caterpillar -- 7.4 Fleet assignment at Delta Airlines -- 7.5 KeyCorp service excellence management System (SEMS) -- 7.6 Summary -- 8: Future trends of operations research -- 8.1 New OR paradigms, techniques, and tools -- 8.2 Revenue management (RM) -- 8.3 Heuristics and metaheuristics --8.4 OR in sport -- 8.5 Summary.

"Operations research (OR) is a critical area of study for any aspiring engineer or professional in the field of operations management. It provides a deep understanding of the fundamental principles and techniques that govern the optimization of complex systems and decision-making processes in various fields, including logistics, manufacturing, finance, and healthcare.
This book is a comprehensive guide to Operations Research, covering a range of topics from the basics of OR and optimization techniques to more advanced concepts such as simulation modeling and analysis, implementation and evaluation of OR solutions, and the challenges and applications of OR in real-world problems.
The first chapter provides an introduction to Operations Research, exploring its historical development and relevance to modern operations management. The second chapter delves into optimization techniques in OR, examining various methods for solving linear and nonlinear optimization problems, such as linear programming (LP), integer programming (IP), and nonlinear programming. This chapter covers topics such as duality, sensitivity analysis, and applications of optimization in production planning and scheduling. The third chapter focuses on the relationship between Operations Research and managerial decision-making, covering topics such as decision analysis, risk management, and game theory. The fourth chapter explores simulation modeling and analysis, which is a powerful technique for modeling complex systems and decision-making processes. The fifth chapter focuses on the implementation and evaluation of OR solutions, covering topics such as project management, implementation strategies, and performance evaluation. The sixth chapter examines the challenges of Operations Research inorganizations, covering topics such as data quality, data privacy, and organizational culture. This chapter explores the barriers to implementing OR solutions in organizations and provides guidance on how to overcome them. The seventh chapter provides examples of the applications of Operations Research in real-world problems, covering topics such as logistics, transportation, healthcare, and energy. The final chapter explores the future trends and directions in Operations Research, covering topics such as machine learning, big data, and artificial intelligence (Al).This chapter examines the potential of emerging technologies for advancing OR and discusses the challenges and opportunities of their implementation.
This book is intended for students, scholars, and professionals in the field of operations management, It provides a comprehensive understanding of Operations Research's critical concepts and practices, using a formal and informative writing style. It is a valuable resource for anyone seeking to deepen their understanding of this important field, and by reading this book, you will gain the knowledge and skills required to analyze and solve complex operational problems with confidence"-- Back cover.