Operations Research Integrated Models and Decision Strategies

Abstract

This book presents a comprehensive and systematic exposition of Operations Research (OR), emphasizing its theoretical foundations, methodological frameworks, and wide-ranging applications in business, engineering, and industrial systems. Beginning with an introduction to the meaning, scope, and significance of Operations Research, the text highlights the role of quantitative techniques, data analysis, and model formulation in effective decision-making and optimization. The book extensively covers Linear Programming, including problem formulation, graphical and simplex methods, duality, sensitivity analysis, and real-world applications in resource allocation. Various decision approaches and theories are discussed to address decision-making under certainty, risk, and uncertainty, incorporating decision trees, payoff criteria, neural networks, Markov models, and predictive techniques.

Core operational models such as Inventory Control, Queuing Theory, Transportation, Assignment, and Sequencing Models are presented with mathematical rigor and practical relevance, enabling readers to analyze cost minimization, scheduling, service efficiency, and system optimization problems. Advanced topics including Game Theory, Simulation, Markov Chain Analysis, and Network Analysis with Project Management (PERT/CPM) further extend the analytical toolkit for handling competitive, stochastic, and project-based environments.

Designed with a learner-centric approach, the book integrates conceptual explanations, mathematical formulations, solved examples, and practice problems, making it suitable for undergraduate and postgraduate students of management, engineering, and applied sciences, as well as professionals seeking analytical decision-support tools. Overall, the book serves as a holistic resource for understanding and applying Operations Research techniques to complex real-world problems.