Optimization Methods in Process Engineering

By the end of this course, students will be able to:

1. Understand the fundamental concepts of optimization and its importance in chemical and process engineering.

2. Formulate optimization problems by defining objective functions, decision variables, and constraints relevant to engineering systems.

3. Differentiate between local and global optima, and apply mathematical tools such as gradients and Hessians to characterize optimal points.

4. Apply optimization methods for single-variable and multivariable functions, with or without constraints.

5. Use direct and indirect search methods, including Newton, Quasi-Newton, Gradient, and Simplex algorithms, to locate optimal solutions.

6. Analyze the behavior of objective functions, distinguishing between convex, concave, unimodal, and multimodal surfaces.

7. Solve constrained optimization problems using Linear Programming (LP) techniques and graphical or analytical approaches.

8. Develop algorithmic approaches for solving engineering optimization problems in process design, control, and operation.

9. Implement numerical methods in MATLAB to solve real-world optimization cases in process engineering.

10. Interpret optimization results and apply them to improve energy efficiency, production yield, and cost reduction in industrial systems.