Multi-objective optimization : techniques and applications in chemical engineering /

Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the la...

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Bibliographic Details
Other Authors: Rangaiah, Gade Pandu.
Format: eBook
Language:English
Published: Hackensack, N.J. : World Scientific, ©2009.
Series:Advances in process systems engineering ; v. 1.
Subjects:
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245 0 0 |a Multi-objective optimization :  |b techniques and applications in chemical engineering /  |c editor, Gade Pandu Rangaiah. 
260 |a Hackensack, N.J. :  |b World Scientific,  |c ©2009. 
300 |a 1 online resource (xvii, 435 pages) :  |b illustrations. 
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490 1 |a Advances in process systems engineering ;  |v v. 1 
504 |a Includes bibliographical references and index. 
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505 0 |a Preface; Contents; Chapter 1 Introduction Gade Pandu Rangaiah; 1.1 Process Optimization; 1.2 Multi-Objective Optimization: Basics; 1.3 Multi-Objective Optimization: Methods; 1.4 Alkylation Process Optimization for Two Objectives; 1.4.1 Alkylation Process and its Model; 1.4.2 Multi-Objective Optimization Results and Discussion; 1.5 Scope and Organization of the Book; References; Exercises; Chapter 2 Multi-Objective Optimization Applications in Chemical Engineering Masuduzzaman and Gade Pandu Rangaiah; Abstract; 2.1 Introduction; 2.2 Process Design and Operation. 
505 8 |a 2.3 Biotechnology and Food Industry2.4 Petroleum Refining and Petrochemicals; 2.5 Pharmaceuticals and Other Products/Processes; 2.6 Polymerization; 2.7 Conclusions; References; Chapter 3 Multi-Objective Evolutionary Algorithms: A Review of the State-of-the-Art and some of their Applications in Chemical Engineering Antonio López Jaimes and Carlos A. Coello Coello; Abstract; 3.1 Introduction; 3.2 Basic Concepts; 3.2.1 Pareto Optimality; 3.3 The Early Days; 3.4 Modern MOEAs; 3.5 MOEAs in Chemical Engineering; 3.6 MOEAs Originated in Chemical Engineering. 
505 8 |a 3.6.1 Neighborhood and Archived Genetic Algorithm3.6.2 Criterion Selection MOEAs; 3.6.3 The Jumping Gene Operator; 3.6.4 Multi-Objective Differential Evolution; 3.7 Some Applications Using Well-Known MOEAs; 3.7.1 TYPE I: Optimization of an Industrial Nylon 6 Semi-Batch Reactor; 3.7.2 TYPE I: Optimization of an Industrial Ethylene Reactor; 3.7.3 TYPE II: Optimization of an Industrial Styrene Reactor; 3.7.4 TYPE II: Optimization of an Industrial Hydrocracking Unit; 3.7.5 TYPE III: Optimization of Semi-Batch Reactive Crystallization Process. 
505 8 |a 3.7.6 TYPE III: Optimization of Simulated Moving Bed Process3.7.7 TYPE IV: Biological and Bioinformatics Problems; 3.7.8 TYPE V: Optimization of a Waste Incineration Plant; 3.7.9 TYPE V: Chemical Process Systems Modelling; 3.8 Critical Remarks; 3.9 Additional Resources; 3.10 Future Research; 3.11 Conclusions; Acknowledgements; References; Chapter 4 Multi-Objective Genetic Algorithm and Simulated Annealing with the Jumping Gene Adaptations Manojkumar Ramteke and Santosh K. Gupta; Abstract; 4.1 Introduction; 4.2 Genetic Algorithm (GA); 4.2.1 Simple GA (SGA) for Single-Objective Problems. 
505 8 |a 4.2.2 Multi-Objective Elitist Non-Dominated Sorting GA (NSGA-II) and its JG Adaptations4.2.2.1 Jumping Genes/Transposons (Stryer, 2000); 4.2.2.2 (Variable-Length) Binary-Coded NSGA-II-JG (Kasat and Gupta, 2003); 4.2.2.3 (Fixed-Length) NSGA-II-aJG; 4.2.2.4 NSGA-II-mJG ('modified' JG); 4.2.2.5 NSGA-II-saJG ('specific adapted' JG); 4.2.2.6 NSGA-II-sJG ('specific' JG); 4.3 Simulated Annealing (SA); 4.3.1 Simple Simulated Annealing (SSA) for Single-Objective Problems; 4.3.2 Multi-Objective Simulated Annealing (MOSA). 
520 |a Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed interest, this monograph presents the recent and ongoing research in multi-optimization techniques and their applications in chemical engineering. Following a brief introductio. 
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