Practical Operations Research: Optimization and Decision-Making

In a world of limited resources and competing priorities, making the best decision is not just about intuition—it is about optimization. This course introduces you to the core principles of operations research, demystifying the mathematical and logical frameworks used to solve complex real-world problems. You will transition from guessing the best course of action to systematically modeling and solving decision-making problems. By reading clear explanations and working through practical written scenarios, you will learn how to identify constraints, define objective functions, and select the right optimization techniques to maximize efficiency and minimize costs. What you'll learn: - Understand the fundamental terminology and core concepts of operations research and optimization. - Formulate linear programming models to solve resource allocation, budgeting, and scheduling problems. - Apply network analysis techniques to optimize transportation logistics and project timelines. - Analyze decision-making under uncertainty using probability concepts and basic game theory. - Explore modern computational approaches and algorithms used to automate complex optimization workflows. The course begins with foundational definitions and key terminology before guiding you through classic optimization models, network problems, and modern decision-making frameworks. You will progress from theoretical concepts to practical, step-by-step written exercises that simulate real-world business scenarios. Designed for absolute beginners, this text-based course requires no advanced mathematical background, making operations research accessible to aspiring analysts, managers, and problem solvers. Start reading today to master the science of making optimal decisions.