Numerical Optimization Methods for Chemical Engineering

To design efficient reactors, minimize processing costs, and maximize product yield, chemical engineers must master the mathematical principles of optimization. This text-based course guides you through the core numerical methods used to solve complex engineering design and operational challenges. You will learn how to translate physical chemical processes into robust mathematical models and apply systematic algorithms to find optimal operating conditions. What you'll learn: Understand foundational optimization terminology, objective functions, and constraints; Formulate linear and non-linear optimization problems for chemical systems; Apply numerical algorithms to solve single and multi-variable optimization problems; Implement modern sensitivity analysis to assess model robustness under varying process conditions; Practice solving classic chemical engineering scenarios, including reactor design and distillation column optimization. The course begins with essential mathematical definitions and foundational optimization concepts before progressing to practical process modeling, algorithmic solutions, and real-world engineering scenarios. This course is designed for undergraduate students, graduate researchers, and practicing chemical engineers who want to build a solid foundation in numerical optimization without needing prior advanced programming experience. Begin optimizing your chemical engineering designs today.