Computational Optimization targets graduate seniors and master's level students in chemical engineering and relevant majors. This book introduces modern computational optimization (or mathematical programming) theory and algorithms, optimization modeling techniques, and various optimization applications in chemical engineering and energy systems. A unique feature of this book is that it has a good balance between theory, computation and applications. Presents optimization applications in chemical engineering and energy systems Helps readers understand the basics of modern optimization theory, concepts and algorithms Covers large-scale optimization models for real-world applications Applies optimization techniques to solve application problems INDICE: 1. Introduction and optimization basics2. Linear programming (LP)3. Mixed-integer linear programming (MILP)4. Nonlinear programming (NLP) and dynamic optimization (DO)5. Mixed-integer nonlinear programming (MINLP) and deterministic global optimization6. Stochastic programming7. Robust optimization8. Optimization and big data analytics9. Computation
- ISBN: 978-0-444-64050-5
- Editorial: Elsevier
- Encuadernacion: Rústica
- Páginas: 510
- Fecha Publicación: 01/11/2022
- Nº Volúmenes: 1
- Idioma: Inglés