Operations Research Fundamentals: Mathematical Modeling for Decisions

In today's complex business landscape, making optimal decisions requires more than just intuition—it demands systematic, mathematical analysis. Operations Research provides the framework to translate real-world resource constraints into solvable mathematical models. This course guides you through the core principles of Operations Research, teaching you how to model and solve complex optimization problems. You will transition from understanding basic linear equations to formulating sophisticated models that minimize costs, maximize profits, and streamline logistics. What you'll learn: - Understand the foundational concepts of Operations Research and how to structure decision-making problems. - Formulate linear programming models to optimize resource allocation under strict constraints. - Solve optimization problems using graphical methods and the fundamental mechanics of the Simplex algorithm. - Model transportation and assignment problems to streamline logistics and supply chain distribution. - Analyze project schedules and workflows using network models like CPM and PERT. - Explore modern computational approaches and how mathematical models are solved using software tools. You will start with key terminology and the philosophy of mathematical modeling before progressing to linear programming, transportation algorithms, and network analysis. Each concept is explained through clear, step-by-step written scenarios and practical business formulations. This course is designed for beginners in business, engineering, and data analysis who want to build a strong foundation in optimization without needing advanced mathematical prerequisites. Start reading today to master the mathematical frameworks that drive efficient operations and strategic decisions.