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Optimization in polymer processing / editors, António Gaspar-Cunha and José António Covas, editors.

Contributor(s): Material type: TextTextSeries: Chemical engineering methods and technologyPublisher: New York : Nova Science Publishers, Inc., [2011]Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781613247464
  • 161324746X
Subject(s): Genre/Form: Additional physical formats: Print version:: Optimization in polymer processingDDC classification:
  • 668.4 22
LOC classification:
  • TP1120
Online resources:
Contents:
OPTIMIZATION IN POLYMER PROCESSING ; OPTIMIZATION IN POLYMER PROCESSING ; CONTENTS ; PREFACE ; INTRODUCTION ; OPTIMIZATION IN ENGINEERING ; AN INTRODUCTION TO OPTIMIZATION; 1 Introduction; 2 Mathematical Formulation; 3 Continuous and Discrete Optimization; 4 Global and Local Optimization and Convexity; 5 Optimality Conditions; 5.1 Unconstrained problems; 5.2 Constrained problems; 6 Heuristics and Metaheuristics; 7 Conclusion; References; AN INTRODUCTION TO MULTIOBJECTIVE OPTIMIZATION TECHNIQUES; 1 Introduction; 2 Notions of Optimality in MOPs; 3 Mathematical Programming Techniques.
3.1 A Priori Preference Articulation3.1.1 Goal Programming; 3.1.2 Goal-Attainment Method; 3.1.3 Lexicographic Method; 3.2 A Posteriori Preference Articulation; 3.2.1 Linear Combination of Weights; 3.2.2 Normal Boundary Intersection; 3.2.3 e-Constraint Method; 3.2.4 Method of Weighted Metrics; 3.3 Interactive Preference Articulation; 3.3.1 Method of Geoffrion-Dyer-Feinberg (GDF); 3.3.2 Tchebycheff Method; 3.3.3 Reference Point Methods; 3.3.4 Light Beam Search; 4 Evolutionary Algorithms; 4.1 MOGA; 4.2 NSGA and NSGA-II; 4.3 SPEA and SPEA2; 4.4 PAES; 4.5 PESA; 4.6 New Trends in MOEAs.
4.7 Incorporation of Preferences in MOEAs4.8 New Trends in the Incorporation of Preferences in MOEAs; 5 Conclusion; References; EXTENDING OPTIMIZATION ALGORITHMS TO COMPLEX ENGINEERING PROBLEMS ; 1. INTRODUCTION ; 2. THE METHODOLOGY ; 2.1. Methodology Structure ; 2.2. Multi-Objective Evolutionary Algorithms ; 3. DECISION MAKING ; 3.1. Current Methods ; 2.2. Weighted Stress Function Method ; 3. ROBUSTNESS ; 4. MEMETIC ALGORITHMS ; 4.1. General Concepts ; 4.2. Coupling MOEAs to a Local Search Method ; 5. Application Examples ; Decision Making ; Robustness ; Memetic Algorithm ; CONCLUSION.
1. INTRODUCTION 2. REACTIVE EXTRUSION MODELING ; 2.1. Concepts ; Flow in the Twin Screw Extruder ; Chemical Reaction ; Rheokinetics ; Coupling the Various Modules; Open Challenges to Model Reactive Extrusion ; 2.2.-caprolactone Polymerization ; 2.3. Starch Cationization ; 3. EXAMPLES OF THE OPTIMIZATION OF REACTIVE EXTRUSION ; 3.1. Optimization Algorithm ; 3.2.-Caprolactone Polymerization ; 3.3. Starch Cationization ; CONCLUSION ; REFERENCES ; THE AUTOMATIC DESIGN OF EXTRUSION DIES AND CALIBRATION/COOLING SYSTEMS ; 1. INTRODUCTION ; 2. STATE-OF-THE-ART ; 3. OPTIMIZATION METHODOLOGY.
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eBook eBook e-Library EBSCO Technology Available
Total holds: 0

Includes bibliographical references and index.

Description based on print version record and CIP data provided by publisher.

English.

OPTIMIZATION IN POLYMER PROCESSING ; OPTIMIZATION IN POLYMER PROCESSING ; CONTENTS ; PREFACE ; INTRODUCTION ; OPTIMIZATION IN ENGINEERING ; AN INTRODUCTION TO OPTIMIZATION; 1 Introduction; 2 Mathematical Formulation; 3 Continuous and Discrete Optimization; 4 Global and Local Optimization and Convexity; 5 Optimality Conditions; 5.1 Unconstrained problems; 5.2 Constrained problems; 6 Heuristics and Metaheuristics; 7 Conclusion; References; AN INTRODUCTION TO MULTIOBJECTIVE OPTIMIZATION TECHNIQUES; 1 Introduction; 2 Notions of Optimality in MOPs; 3 Mathematical Programming Techniques.

3.1 A Priori Preference Articulation3.1.1 Goal Programming; 3.1.2 Goal-Attainment Method; 3.1.3 Lexicographic Method; 3.2 A Posteriori Preference Articulation; 3.2.1 Linear Combination of Weights; 3.2.2 Normal Boundary Intersection; 3.2.3 e-Constraint Method; 3.2.4 Method of Weighted Metrics; 3.3 Interactive Preference Articulation; 3.3.1 Method of Geoffrion-Dyer-Feinberg (GDF); 3.3.2 Tchebycheff Method; 3.3.3 Reference Point Methods; 3.3.4 Light Beam Search; 4 Evolutionary Algorithms; 4.1 MOGA; 4.2 NSGA and NSGA-II; 4.3 SPEA and SPEA2; 4.4 PAES; 4.5 PESA; 4.6 New Trends in MOEAs.

4.7 Incorporation of Preferences in MOEAs4.8 New Trends in the Incorporation of Preferences in MOEAs; 5 Conclusion; References; EXTENDING OPTIMIZATION ALGORITHMS TO COMPLEX ENGINEERING PROBLEMS ; 1. INTRODUCTION ; 2. THE METHODOLOGY ; 2.1. Methodology Structure ; 2.2. Multi-Objective Evolutionary Algorithms ; 3. DECISION MAKING ; 3.1. Current Methods ; 2.2. Weighted Stress Function Method ; 3. ROBUSTNESS ; 4. MEMETIC ALGORITHMS ; 4.1. General Concepts ; 4.2. Coupling MOEAs to a Local Search Method ; 5. Application Examples ; Decision Making ; Robustness ; Memetic Algorithm ; CONCLUSION.

1. INTRODUCTION 2. REACTIVE EXTRUSION MODELING ; 2.1. Concepts ; Flow in the Twin Screw Extruder ; Chemical Reaction ; Rheokinetics ; Coupling the Various Modules; Open Challenges to Model Reactive Extrusion ; 2.2.-caprolactone Polymerization ; 2.3. Starch Cationization ; 3. EXAMPLES OF THE OPTIMIZATION OF REACTIVE EXTRUSION ; 3.1. Optimization Algorithm ; 3.2.-Caprolactone Polymerization ; 3.3. Starch Cationization ; CONCLUSION ; REFERENCES ; THE AUTOMATIC DESIGN OF EXTRUSION DIES AND CALIBRATION/COOLING SYSTEMS ; 1. INTRODUCTION ; 2. STATE-OF-THE-ART ; 3. OPTIMIZATION METHODOLOGY.

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