Industrial Engineering Foundations: Linear Programming and Queuing Theory

Industrial and production systems rely on mathematical optimization to minimize operational costs and maximize efficiency. Understanding how to model these systems is the key to solving real-world engineering bottlenecks and streamlining workflows. This text-based course guides you from foundational industrial engineering concepts to practical optimization techniques. You will learn to formulate mathematical models, analyze waiting lines, and apply systematic decision-making workflows to complex operational problems. What you'll learn: - Understand the fundamental principles of industrial engineering and operations research. - Formulate and solve Linear Programming Problems using graphical and simplex methods. - Analyze queuing systems and apply Queuing Theory to minimize waiting times and optimize service capacity. - Apply modern data-driven decision-making frameworks to production and inventory challenges. - Evaluate operational bottlenecks using systematic mathematical modeling techniques. The course starts with essential terminology and the mathematical foundations of optimization. You will then progress through step-by-step written analyses of linear programming, simplex algorithms, and queuing models, complete with practical engineering scenarios to solidify your understanding. This course is designed for engineering students, operations analysts, and beginners looking to build a strong foundation in industrial engineering without any prior advanced modeling experience. Start mastering the mathematical core of industrial engineering today.