Multi-Objective Optimization in Chemical Engineering (eBook, PDF)

Developments and Applications
Redaktion: Rangaiah, Gade Pandu; Bonilla-Petriciolet, Adrian

• Format: PDF

Produktbeschreibung

For reasons both financial and environmental, there is a perpetual need to optimize the design and operating conditions of industrial process systems in order to improve their performance, energy efficiency, profitability, safety and reliability. However, with most chemical engineering application problems having many variables with complex inter-relationships, meeting these optimization objectives can be challenging. This is where Multi-Objective Optimization (MOO) is useful to find the optimal trade-offs among two or more conflicting objectives. This book provides an overview of the recent developments and applications of MOO for modeling, design and operation of chemical, petrochemical, pharmaceutical, energy and related processes. It then covers important theoretical and computational developments as well as specific applications such as metabolic reaction networks, chromatographic systems, CO2 emissions targeting for petroleum refining units, ecodesign of chemical processes, ethanol purification and cumene process design. Multi-Objective Optimization in Chemical Engineering: Developments and Applications is an invaluable resource for researchers and graduate students in chemical engineering as well as industrial practitioners and engineers involved in process design, modeling and optimization.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 528
• Erscheinungstermin: 20. März 2013
• Englisch
• ISBN-13: 9781118341698
• Artikelnr.: 38263572

Autorenporträt

Gade Pandu Rangaiah has been with the National University of Singapore since 1982, and is Professor in the Department of Chemical & Biomolecular Engineering. His research interests are in control, modeling and optimization of chemical, petrochemical and related processes. Prof. Rangaiah published 130 papers in international journals and presented around 100 papers in conferences. He has received several awards for his teaching including Annual Teaching Excellence Awards from NUS for four consecutive years. He has edited two books for World Scientific, and has one book in production with Wiley. Adrian Bonilla-Petriciolet has been with the Instituto Tecnologico de Aguascalientes, Mexico, since 2001 and is currently Professor in the Department of Chemical Engineering and Head of Research Programs. His research interests include stochastic global optimization, applied thermodynamics, modeling and optimization of chemical processes. He has published more than 30 papers in international journals and refereed conference proceedings in the broad areas of process modeling and optimization.

Inhaltsangabe

Preface xv Part I Overview 1 Introduction 3 Adrian Bonilla-Petriciolet and
Gade Pandu Rangaiah 1.1 Optimization and Chemical Engineering 3 1.2 Basic
Definitions and Concepts of Multi-Objective Optimization 5 1.3
Multi-Objective Optimization in Chemical Engineering 8 1.4 Scope and
Organization of the Book 9 2 Optimization of Pooling Problems for Two
Objectives Using the epsilon-Constraint Method 17 Haibo Zhang and Gade
Pandu Rangaiah 2.1 Introduction 17 2.2 Pooling Problem Description and
Formulations 19 2.3 epsilon-Constraint Method and IDE Algorithm 25 2.4
Application to Pooling Problems 27 2.5 Results and Discussion 28 2.6
Conclusions 32 3 Multi-objective Optimization Applications in Chemical
Engineering 35 Shivom Sharma and Gade Pandu Rangaiah 3.1 Introduction 35
3.2 Multi-Objective Optimization Applications in Process Design and
Operation 37 3.3 Multi-Objective Optimization Applications in Petroleum
Refining, Petrochemicals, and Polymerization 57 3.4 Multi-Objective
Optimization Applications in the Food Industry, Biotechnology, and
Pharmaceuticals 57 3.5 Multi-Objective Optimization Applications in Power
Generation and Carbon Dioxide Emissions 66 3.6 Multi-Objective Optimization
Applications in Renewable Energy 66 3.7 MOO Applications in Hydrogen
Production and Fuel Cells 82 3.8 Conclusions 82 Part II Multi-Objective
Optimization Developments 4 Performance Comparison of Jumping-Gene
Adaptations of the Elitist Nondominated Sorting Genetic Algorithm 105
Shivom Sharma, Seyed Reza Nabavi and Gade Pandu Rangaiah 4.1 Introduction
105 4.2 Jumping-Gene Adaptations 107 4.3 Termination Criterion 110 4.4
Constraints Handling and Implementation of Programs 112 4.5 Performance
Comparison 114 4.6 Conclusions 124 5 Improved Constraint Handling Technique
for Multi-objective Optimization with Application to Two Fermentation
Processes 129 Shivom Sharma and Gade Pandu Rangaiah 5.1 Introduction 129
5.2 Constraint Handling Approaches in Chemical Engineering 131 5.3 Adaptive
Constraint Relaxation and Feasibility Approach for SOO 132 5.4 Adaptive
Relaxation of Constraints and Feasibility Approach for MOO 133 5.5 Testing
of MODE-ACRFA 136 5.6 Multi-Objective Optimization of the Fermentation
Process 139 5.7 Conclusions 153 6 Robust Multi-Objective Genetic Algorithm
(RMOGA) with Online Approximation under Interval Uncertainty 157 Weiwei Hu,
Adeel Butt, Ali Almansoori, Shapour Azarm and Ali Elkamel 6.1 Introduction
157 6.2 Background and Definition 159 6.3 Robust Multi-Objective Genetic
Algorithm (RMOGA) 163 6.4 Online Approximation-Assisted RMOGA 168 6.5 Case
Studies 172 6.6 Conclusion 178 7 Chance Constrained Programming to Handle
Uncertainty in Nonlinear Process Models 183 Kishalay Mitra 7.1 Introduction
183 7.2 Uncertainty Handling Techniques 184 7.3 Chance-Constrained
Programming: Fundamentals 186 7.4 Industrial Case Study: Grinding 193 7.5
Conclusion 206 8 Fuzzy Multi-objective Optimization for Metabolic Reaction
Networks by Mixed-Integer Hybrid Differential Evolution 217 Feng-Sheng Wang
and Wu-Hsiung Wu 8.1 Introduction 217 8.2 Problem Formulation 219 8.3
Optimality 223 8.4 Mixed-Integer Hybrid Differential Evolution 228 8.5
Examples 233 8.6 Summary 240 Part III Chemical Engineering Applications 9
Parameter Estimation in Phase Equilibria Calculations using Multi-Objective
Evolutionary Algorithms 249 Sameer Punnapala, Francisco M. Vargas and Ali
Elkamel 9.1 Introduction 249 9.2 Particle Swarm Optimization (PSO) 250 9.3
Parameter Estimation in Phase Equilibria Calculations 253 9.4 Model
Description 253 9.5 Multi-Objective Optimization Results and Discussions
256 9.6 Conclusions 260 10 Phase Equilibrium Data Reconciliation using
Multi-Objective Differential Evolution with Tabu List 267 A.
Bonilla-Petriciolet, Shivom Sharma and Gade Pandu Rangaiah 10.1
Introduction. 267 10.2 Formulation of the Data-Reconciliation Problem for
Phase Equilibrium Modeling 270 10.3 Multi-Objective Optimization using
Differential Evolution with Tabu List 274 10.4 Data Reconciliation of
Vapor-Liquid Equilibrium by MOO 277 10.5 Conclusions 287 11 CO2 Emissions
Targeting for Petroleum Refinery Optimization 293 Mohmmad A. Al-Mayyahi,
Andrew F.A. Hoadley and Gade Pandu Rangaiah 11.1 Introduction 293 11.2
MOO-Pinch Analysis Framework to Target CO2 Emissions 303 11.3 Case Studies
304 11.4 Case Studies 305 11.5 Conclusions 315 12 Ecodesign of Chemical
Processes with Multi-Objective Genetic Algorithms 335 Catherine
Azzaro-Pantel and Luc Pibouleau 12.1 Introduction 335 12.2 Numerical Tools
337 12.3 Williams-Otto Process (WOP) Optimization for Multiple Economic and
Environmental Objectives 338 12.4 Revisiting the HDA Process 346 12.5
Conclusions and Perspectives 361 13 Modeling and Multi-objective
Optimization of a Chromatographic System 369 Abhijit Tarafder 13.1
Introduction 369 13.2 Chromatography--Some Facts 371 13.3 Modeling
Chromatographic Systems 373 13.4 Solving the Model Equations 376 13.5 Steps
for Model Characterization 377 13.6 Description of the Optimization
Routine--NSGA-II 387 13.7 Optimization of a Binary Separation in
Chromatography 387 13.8 An Example Study 390 13.9 Conclusion 396 14
Estimation of Crystal Size Distribution: Image Thresholding based on
Multi-Objective Optimization 399 Karthik Raja Periasamy and S.
Lakshminarayanan 14.1 Introduction 399 14.2 Methodology 401 14.3 Image
Simulation 402 14.4 Image Preprocessing 404 14.5 Image Segmentation 404
14.6 Feature Extraction 413 14.7 Future Work 417 14.8 Conclusions 418 15
Multi-Objective Optimization of a Hybrid Steam Stripper-Membrane Process
for Continuous Bioethanol Purification 423 Krishna Gudena, Gade Pandu
Rangaiah and S Lakshminarayanan 15.1 Introduction 423 15.2 Description and
Design of a Hybrid Stripper-Membrane System 426 15.3 Mathematical
Formulation and Optimization 431 15.4 Results and Discussion 435 15.5
Conclusions 445 15.5 Exercises 445 16 Process Design for Economic,
Environmental and Safety Objectives with an Application to the Cumene
Process 449 Shivom Sharma, Zi Chao Lim and Gade Pandu Rangaiah 16.1
Introduction 449 16.2 Review and Calculation of Safety Indices 451 16.3
Cumene Process, its Simulation and Costing 455 16.4 I2SI Calculation for
Cumene Process 459 16.5 Optimization using EMOO Program 462 16.6
Optimization for Two Objectives 464 16.7 Optimization for EES Objectives
469 16.8 Conclusions 471 17 New PI Controller Tuning Methods Using
Multi-Objective Optimization 479 Allan Vandervoort, Jules Thibault and Yash
Gupta 17.1 Introduction 479 17.2 PI Controller Model 480 17.3 Optimization
Problem 481 17.4 Pareto Domain 481 17.5 Optimization Results 488 17.6
Controller Tuning 490 17.7 Application of the Tuning Methods 491 17.8
Conclusions 498 Index