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Optimization of Process Flowsheets through Metaheuristic Techniques - 
      José María Ponce-Ortega
    
      Luis Germán Hernández-Pérez

Optimization of Process Flowsheets through Metaheuristic Techniques

; Luis Germán Hernández-Pérez

This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus (R), HYSIS (R), Super Pro Designer (R) linked to a variety of metaheuristic techniques implemented in Matlab (R), Excel (R), C++, and others, eliminating the numerical complications through the optimization process. Les mer
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This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus (R), HYSIS (R), Super Pro Designer (R) linked to a variety of metaheuristic techniques implemented in Matlab (R), Excel (R), C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process.

Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab (R) routines are included as electronic supporting material.
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Utgitt:
Forlag: Springer Nature Switzerland AG
Innbinding: Paperback
Språk: Engelsk
Sider: 110
ISBN: 9783030062842
Format: 24 x 16 cm
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1. Basic Concepts

1.1. Process Simulation

1.1.1. Introduction to Process Simulation

1.1.2. Simulation Software

1.1.3. Aspen Plus

1.1.4. Superpro Designer

1.2. Searching Methods

1.2.1. Optimization Definitions

1.2.2. Classification of Searching Methods

1.2.3. Deterministic Algorithms

1.3. Interaction Between Programs

1.3.1. Definitions for the Software Link

1.4. Nomenclature



2. General Methodology to Link Process Simulators to Optimization

2.1. Nomenclature



3. Process Simulation Software

3.1. Using Aspen Plus

3.2. Example Of The Conventional Rankine Cycle

3.3. Using Superpro Designer

3.4. Process Simulation Exercises



4. Stochastic Optimization Methods

4.1. Simulated Annealing

4.2. Genetic Algorithms

4.2.1. Example of Codification

4.2.2. Management of Restrictions

4.3. Using Ga Toolbox of Matlab

4.4. Stochastic Hybrids Algorithms

4.5. Using I-Mode in MS Excel

4.5.1. Main Program Interface

4.5.2. Objectives and Constrains

4.6. Stochastic Optimization Exercises

4.7. Nomenclature



5. Linking Programs

5.1. Introduction to Link Between Process Simulators and Optimization Routines

5.2. Previous Knowledge

5.2.1. MS Excel Configuration

5.2.2. Object Name of the Simulator File

5.3. Link Between Aspen Plus and MS Excel

5.3.1. Sub-Routine to Link Aspen Plus and MS Excel

5.3.2. Files to Link Aspen Plus and MS Excel

5.3.3. Call Name of Aspen Plus Variables

5.4. Link Between Superpro Designer (R) and MS Excel (R)

5.4.1. Sub-Routine to Link Superpro Designer (R) and MS Excel (R)

5.4.2. Files to Link Superpro Designer (R) and MS Excel (R)

5.4.3. Call Name of Superpro Designer Variables

5.5. Link Between MS Excel (R) and Matlab (R)

5.5.1. Sub-Routine to Link MS Excel (R) and Matlab (R)

5.5.2. Files Needed to Link MS Excel (R) and Matlab (R)

5.5.3. Object Name of the Linker Program File

5.5.4. Optimization Parameters Specification In Matlab (R)

5.6. Nomenclature



6. Example of Generation Power Plant

6.1. Problem Statement

6.2. Model Formulation

6.2.1. Model Simulation Using the Aspen Plus (R) Software

6.2.2. Mathematical Formulation

6.2.3. Definition of The Objective Functions

6.2.4. Economic Objective Function

6.2.5. Environmental Objective Function

6.3. Stochastic Optimization Algorithm Used

6.4. Link Between The Process Simulator And Optimization Algorithm

6.5. Results

6.6. Exercises

6.7. Nomenclature




7. Conclusions



8. Bibliography




9. Appendix

a. APPENDIX A: Code for the Link Between Aspen Plus and MS Excel (R)

b. APPENDIX B: Code for the Link Between SuperPro Designer (R) and MS Excel (R)

c. APPENDIX C: Code for the Link Between MS Excel (R) and Matlab (R)

- Prof. Dr. Jose Maria Ponce-Ortega got his Ph.D. and Master degrees in Chemical Engineering at the Institute of Technology of Celaya, Mexico, in 2009 and 2003, respectively. He stayed as a postdoctoral researcher at Texas A&M University and also as visiting scholar in Carnegie Mellon University. Dr. Ponce-Ortega is currently full professor at the Universidad Michoacana de San Nicolas de Hidalgo, Mexico, and he is member of the National Research System of Mexico. The main research interests of Dr. Ponce-Ortega are optimization of chemical processes, sustainable design, energy, mass, water and property integration and supply chain optimization. Dr. Ponce-Ortega has published more than 180 papers, 1 book and 46 book chapters.

- Luis German Hernandez-Perez got his Master and Bachelor degrees in Chemical Engineering at Universidad Michoacana de San Nicolas de Hidalgo, Mexico. His current research project as a Ph.D. student involves the use of metaheuristic techniques linked with process simulators for optimization chemical processes.