Operations Research: Optimization and Mathematical Modeling

In a world of limited resources, the ability to make the most efficient choice is a critical skill for any professional. This course provides a comprehensive introduction to Operations Research, the science of making better decisions through mathematical modeling. You will learn to identify optimization opportunities and transform them into structured models that drive efficiency. By the end of this course, you will be able to apply rigorous mathematical frameworks to solve resource allocation, logistics, and production challenges. What you'll learn: - Understand the fundamental terminology and core principles of optimization. - Build linear programming models to represent real-world constraints and goals. - Master the Simplex method and the logic behind algorithmic solutions. - Apply duality theory and sensitivity analysis to test model robustness. - Practice solving transportation and network flow problems. - Explore integer programming for scenarios requiring discrete outcomes. The curriculum begins with essential definitions and foundational concepts before moving into practical modeling techniques and algorithmic theories. This structured text-based approach ensures you build a solid foundation in mathematical programming through clear explanations and written exercises. This course is designed for beginners and students who want to develop analytical problem-solving skills without any previous background in operations research. Start mastering the mathematical tools used to optimize modern industries today.