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Optimization of Chemical Processes

A Sustainable Perspective

verfasst von: José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Verlag: Springer Nature Switzerland

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This textbook introduces readers to a comprehensive framework for the application of deterministic optimization strategies in the field of chemical processes, with a strong emphasis on sustainability.

The book establishes a vital connection between fundamental deterministic optimization principles, optimization tools, and real-world application instances, all within the context of environmentally responsible practices. The approach put forth in this book is exceptionally versatile, allowing for the use of many optimization software and deterministic techniques.

Contained in the book are many fundamental optimization concepts, encompassing linear programming, nonlinear programming, integer programming, and multi-objective optimization, all tailored to promote sustainable decision-making. Furthermore, the book provides practical examples illustrating the application of these techniques within sustainable chemical processes as tutorials.

The textbook also explores the utilization of popular optimization software platforms such as GAMS, MATLAB, and Python, demonstrating how these tools can be leveraged for eco-friendly process optimization. Through this comprehensive framework, readers can not only acquire the skills needed to optimize a wide range of processes but also learn how to do so with sustainability at the forefront of their considerations. This approach streamlines the optimization process, eliminating unnecessary complications along the way and ensuring that environmental and ethical considerations are integral to the decision-making process.

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Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

This chapter presents an introduction to the optimization. This chapter presents an introduction to the development optimization models for different types of process devices. A proper analysis of the degrees of freedom of process units, as well as for entire processes is presented in this chapter. The concept of superstructure is analyzed, and the basics of development optimization formulations are presented. The classification for the different types of optimization formulations is presented and the basic techniques to solve these problems are addressed in this chapter. Also, this chapter presents the definitions of the different types of optimization formulations mainly associated with chemical processes. Finally, this chapter also presents basic mathematical concepts needed to solve optimization problems.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 2. Unconstrained Optimization

Abstract

This chapter introduces basic concepts about unconstrained optimization. It then addresses methods for solving univariable optimization problems, including those based on the first and second derivatives. Techniques for tackling unconstrained multivariable optimization problems are also explored. Several examples are presented and solved iteratively to demonstrate how these techniques work. Finally, the proposed examples are solved using different software, such as GAMS, Matlab, and Python.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 3. Linear Programming

Abstract

This chapter presents first an introduction to modeling and representing linear programming optimization problems, then the simplex method is explained step-by-step. Several examples are solved using a clear explanation of the simplex method to have a proper understating of this method. Then, these problems are solved using commercial software, which includes solutions through GAMS, Matlab, and Python.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 4. Non-linear Programming

Abstract

This chapter delves into nonlinear programming theory, initially presenting its basic concepts before exploring various optimization methods for nonlinear problems. It emphasizes the practical application of these methods, highlighting the use of software tools like GAMS, Matlab, and Python for problem-solving. The chapter culminates with a real-world example, demonstrating the selection of an energy source for a refrigeration system using GAMS, thereby bridging the gap between theoretical principles and practical applications in a succinct yet comprehensive manner.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 5. Integer Programming

Abstract

The chapter delves into Integer Programming, starting with an introduction to its use and the significance of binary variables in modeling decisions and constraints. It explores how to model propositions and disjunctions using binary variables, reviews methods for solving integer optimization problems, presents practical examples of Mixed Integer Linear Programming (MILP) problems, and concludes with the implementation of these examples using computational tools, thereby providing a comprehensive view from theory to practical application.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 6. Multi-objective Optimization

Abstract

This chapter presents an introduction to multi-objective optimization. First, the basic concepts are presented, and then several solution approaches are described and exemplified through several examples. In particular, the epsilon-constraint method is presented, together with the weighting approach, as well as a multistakeholder formulation. Similarly, to obtain a fair solution, the concepts of Nash, Rawlsian, and social welfare approaches are described. A case study for the optimal distribution of vaccines under emergency constraints (pandemic conditions) is presented and discussed. Furthermore, the GAMS code is presented in this chapter.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 7. Optimization Under Uncertainty

Abstract

This chapter presents an introduction to the optimization under uncertainty. This chapter introduces parameters that are unknown in optimization problems, where there is a need to use statistical functions to properly obtain stable solutions. Several mathematical formulations are presented to generally solve optimization problems under uncertainty associated with specific parameters in the models. Also, a case study for designing a system where there is involved a lot of uncertainty is presented, this problem is analyzed in detail to show the importance of considering the uncertainty in the optimization problems.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 8. Optimal Synthesis of Water Networks

Abstract

This chapter presents several applications of optimization to the synthesis of water networks under different conditions. First, a direct recycle formulation for the synthesis of water networks is presented, this has the advantage of corresponding to a linear programming mode, and with low investment can produce a significant reduction in the cost, freshwater consumption, and wastewater discharged to the environment. Then a simplified approach based on a linearized formulation for a recycle and reuse configuration is presented, and finally, a novel formulation based on properties for the synthesis of water networks is presented. Several case studies are presented and discussed, also the GAMS codes are presented.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 9. Optimal Synthesis of Heat Exchanger Networks

Abstract

This chapter presents an introduction to energy integration between process streams for waste heat recovery and process integration. Then several approaches for optimally integrating the energy of process streams are presented. Particularly, the transshipment model, the extended transshipment model, and the synheat and isosynheat formulations are discussed. Several examples are presented to show the applicability of these approaches. Furthermore, the corresponding GAMS codes are presented for implementation to solve different cases.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 10. Optimal Synthesis of Eco-industrial Parks

Abstract

This chapter presents an introduction to the water and energy integration into an eco-industrial park. First, the concepts associated with industrial symbiosis are presented. Then several optimization approaches for water integration into an eco-industrial park are presented. Then, some optimization formulations for the energy integration between different industrial processes are described. These approaches include direct recycling, exchanges between the different plants, and the possibility of installing a central shared facility to treat the waste streams. The application of the proposed optimization formulations is shown through several examples problems.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 11. Software: Tools for Optimization

Abstract

This chapter emphasizes the importance of integrating optimization tools in engineering education, it enhances students’ knowledge and skills to tackle complex challenges, and it devises innovative solutions. The integration of mathematical programming and languages similar to GAMS, PYTHON, or MATLAB benefits Process Systems Engineering, enabling the translation of abstract concepts into practical solutions. These tools bridge theory and real-world application, particularly in the chemical engineering process design field. This chapter also highlights the essential role of these tools in education, preparing students to achieve a significant impact in engineering.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 12. Optimization Using the General Algebraic Modeling System (GAMS)

Abstract

This chapter is a practical guide designed to help students learn and effectively use GAMS (General Algebraic Modeling System). GAMS is an algebraic modeling language widely used in mathematical optimization and decision-making. The chapter begins with an introduction to the basic concepts of GAMS, presenting its syntax and structure. Afterward, the fundamental parts of a GAMS program are explored, including the declaration of sets, variables, parameters, and constraints. The different structures that allow for more efficient programming in GAMS are explained in detail along with practical, simple examples presented, and with techniques for optimizing and solving these models are shown.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 13. Optimization Using the Software MATLAB

Abstract

This chapter serves as a practical guide for utilizing MATLAB as a powerful tool in the resolution of optimization problems. MATLAB, renowned for its numerical computing capabilities, features a distinctive matrix-oriented programming language that holds great appeal for engineers and scientists engaged in tasks such as modeling, data analysis, and algorithm development. Moreover, MATLAB offers an array of integrated tools, enabling the creation of 2D and 3D graphics, animations, and diverse visualizations. Specifically tailored for optimization tasks, the Optimization Toolbox within MATLAB facilitates the minimization or maximization of functions, accommodating constraints in both continuous and discrete problem domains. Within the pages of this chapter, readers will gain proficiency in solving optimization problems through the implementation of MATLAB. The focus is on equipping readers with the skills to compose, execute, and troubleshoot code using MATLAB and its associated tools.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Chapter 14. Optimization Using the Software Phyton with Spyder

Abstract

This chapter serves as a practical guide for utilizing Python, specifically within the Spyder IDE, as a powerful computational tool for optimization. Python, a versatile programming language widely used in mathematical modeling and decision-making, provides a solid foundation for optimization tasks. Core elements like variables, loops, and conditional statements are covered to facilitate efficient program construction. The Spyder IDE is recommended as an optimal environment for Python programming; Its user-friendly interface and features for scientific computing enhance the optimization experience. Readers learn how to write, execute, and debug optimization programs effectively using Spyder. Various Python libraries are introduced, such as NumPy, Matplotlib, and GEKKO, which bolster optimization capabilities. These libraries enable efficient data handling, mathematical computations, and advanced optimization algorithms. The chapter focuses on formulating and representing optimization models using Python.

José María Ponce-Ortega, Rogelio Ochoa-Barragán, César Ramírez-Márquez

Titel: Optimization of Chemical Processes
verfasst von: José María Ponce-Ortega
Rogelio Ochoa-Barragán
César Ramírez-Márquez
Copyright-Jahr: 2024
Verlag: Springer Nature Switzerland
Electronic ISBN: 978-3-031-57270-8
Print ISBN: 978-3-031-57269-2
DOI: https://doi.org/10.1007/978-3-031-57270-8

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