Grossmann I. Advanced Optimization for Process Systems Engineering 2021

Textbook in PDF format

Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering.
Optimization in Process Systems Engineering
Solving Nonlinear Equations
Basic Theoretical Concepts in Optimization
Nonlinear Programming Algorithms
Linear Programming
Mixed-Integer Programming Models
Systematic Modeling of Constraints with Logic
Mixed-Integer Linear Programming
Mixed-Integer Nonlinear Programming
Generalized Disjunctive Programming
Constraint Programming
Nonconvex Optimization
Lagrangean Decomposition
Stochastic Programming
Flexibility Analysis