Operations Research: Formulating Business Optimization Models

Business leaders and analysts constantly face the challenge of making the best use of limited resources, whether it is budget, inventory, or personnel. This written course shows you how to turn these complex decision-making challenges into clear, solvable mathematical models. You will transition from intuitive decision-making to structured, data-driven optimization. By understanding how to define decision variables, constraints, and objective functions, you will gain the skills to mathematically represent and solve real-world business scenarios, preparing you for modern analytical roles. What you'll learn: - Understand the fundamental terminology, concepts, and history of operations research. - Formulate linear programming models to solve resource allocation and production planning challenges. - Define objective functions, decision variables, and constraints for diverse business scenarios. - Analyze network flow and transportation problems to optimize logistics and supply chains. - Apply sensitivity analysis to understand how changes in real-world data affect your optimal solutions. - Explore modern computational workflows for translating mathematical formulations into computer-solvable code. The course begins with foundational definitions and basic modeling concepts before guiding you through progressively complex formulations, including integer programming and network models. You will practice these concepts through written step-by-step exercises and realistic business scenarios. This course is designed for beginners in business analysis, engineering, or economics, with no prior optimization background required. Start mastering the mathematical frameworks that drive optimal business decisions today.