Introduction to Operations Research: Linear Programming and Optimization

Every business and organization faces the challenge of allocating limited resources to achieve maximum efficiency and profit. This course introduces you to the core principles of operations research, giving you the analytical tools to make optimal, data-driven decisions. You will transition from intuitive decision-making to structured mathematical optimization, learning how to model real-world constraints and objectives through written explanations and step-by-step scenarios. What you'll learn: - Understand the foundational concepts of operations research and the systematic decision-making process. - Formulate linear programming problems to model real-world business constraints and objectives. - Solve linear models using graphical methods and understand the mechanics of the Simplex algorithm. - Analyze transportation and assignment problems to optimize supply chains and logistics. - Apply sensitivity analysis to understand how changes in variables affect your optimal solutions. - Explore modern computational approaches and software-based optimization concepts used in industry today. The course begins with essential terminology and the philosophy of mathematical modeling before guiding you through linear programming, transportation algorithms, and practical decision-making scenarios. This course is designed for beginners, business analysts, management students, and anyone looking to build a strong foundation in optimization with no prior experience required. Start reading today to master the science of optimal decision-making.