Numerical Optimization in Chemical Engineering

Chemical engineers must constantly make decisions to maximize yields, minimize costs, and ensure safe, sustainable plant operations. This text-based course guides you through the fundamental mathematical concepts and computational techniques used to solve complex optimization problems in chemical engineering. You will start with the core terminology of objective functions, design variables, and constraints before moving into practical formulation and solution methods. By reading through detailed explanations and studying clean, modern code implementations, you will develop the skills to model and optimize real-world chemical systems. What you will learn: Understand the mathematical foundations of constrained and unconstrained optimization; Formulate objective functions and constraints for chemical reactors, separation columns, and heat exchanger networks; Apply modern numerical algorithms to solve non-linear programming and mixed-integer optimization problems; Analyze sensitivity and evaluate the robustness of optimal operating points; Implement optimization routines using modern, clean Python-based scientific libraries. The course begins with foundational definitions and mathematical prerequisites, then progresses from basic single-variable search methods to multi-variable constrained optimization, concluding with practical process design scenarios. This course is designed for engineering students, researchers, and practicing chemical engineers who want to build a solid foundation in computational optimization without needing prior advanced programming experience. Start optimization of your chemical engineering systems today.