Optimization in Chemical Engineering : Deterministic, Meta-Heuristic and Data-Driven Techniques.

Format:

Book

Author/Creator:

Gómez-Castro, Fernando Israel.

Contributor:

Rico-Ramírez, Vicente.

Series:

De Gruyter Textbook Series

Language:

English

Physical Description:

1 online resource (464 pages)

Edition:

1st ed.

Place of Publication:

Berlin/Boston : Walter de Gruyter GmbH, 2025.

Summary:

Optimization is an area in constant evolution. The search for robust optimization techniques to deal with the highly non-convex models that represent the systems related to Chemical Engineering has led to important advances in the area. The need for developing economically feasible processes which are simultaneously environmentally friendly, safe, and controllable requires for adequate optimization strategies. Moreover, finding a global optimum is still a challenge for a diversity of cases. Thus, this book presents a compilation of classic and emerging optimization techniques, focusing on their application to systems related to the Chemical Engineering. The book shows the applications of classic mathematical programming, metaheuristic optimization methods and machine learning-based strategies. The analysis of the described techniques allows the reader identifying the advantages and disadvantages of each approach. Moreover, the book will discuss the perspectives for future developments on the area.

Contents:

Frontmatter

Contents

List of contributing authors

Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations

Chapter 2 Deterministic optimization of distillation processes

Chapter 3 Optimal design of process energy systems integrating sustainable considerations

Chapter 4 Metaheuristics for the optimization of chemical processes

Chapter 5 Surrogate-based optimization techniques for process systems engineering

Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems

Chapter 7 Applications of Bayesian optimization in chemical engineering

Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications

Chapter 9 Hybrid optimization methodologies for the design of chemical processes

Chapter 10 Optimization under uncertainty in process systems engineering

Chapter 11 Optimal control of batch processes in the continuous time domain

Chapter 12 Supply chain optimization for chemical and biochemical processes

Chapter 13 Future insights for optimization in chemical engineering

Index

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783111383439

3111383431

OCLC:

1511341004