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Global optimization : theory, developments and applications /
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Nova Publishers,
[2013]
|
| Colección: | Mathematics Research Developments
Computational mathematics and analysis series |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- GLOBAL OPTIMIZATION ; Library of Congress Cataloging-in-Publication Data; CONTENTS; PREFACE ; Chapter 1 PARTICLE SWARM OPTIMIZATION WITH RE-INITIALIZATION STRATEGIES FOR CONTINUOUS GLOBAL OPTIMIZATION ; ABSTRACT ; NOMENCLATURE ; 1. INTRODUCTION ; 2. DESCRIPTION AND DEVELOPMENT OF PSO ; 3. PARTICLE SWARM OPTIMIZATION WITH RE-INITIALIZATION STRATEGIES ; 3. 1. PSO with Selection Strategy ; 3. 2. PSO with Escape Strategy ; 3. 3. PSO with Both Selection and Escape Strategies ; 4. RESULTS AND DISCUSSION; 4. 1. Description of Benchmark Problems ; 4. 2. Performance of Proposed PSO.
- 4.3. Comparison of PPSO with Recent PSO Algorithms CONCLUSION ; APPENDIX A: ORTHOGONAL MATRIX ; REFERENCES ; Chapter 2 PARTICLE SWARM GLOBAL OPTIMIZATION OF ORBITAL MANEUVERS ; ABSTRACT ; 1. INTRODUCTION ; 2. DESCRIPTION OF THE METHOD ; 2.1. Unconstrained Optimization; 2.2. Constrained Optimization ; 3. OPTIMAL IMPULSIVE TRANSFERS BETWEEN COPLANAR CIRCULAR ORBITS ; 3.1. Problem Definition ; 3.2. Numerical Results ; 4. OPTIMAL TWO-IMPULSE TRANSFERS BETWEEN NON-COPLANAR ORBITS ; 4.1. Problem Definition ; 4.2. Numerical Results ; 5. OPTIMAL FOUR-IMPULSE ORBITAL RENDEZVOUS.
- 5.1. Problem Definition 5.2. Numerical Results ; 6. OPTIMAL LOW EARTH ORBIT
- LOW MOON ORBIT TRANSFER ; 6.1. Problem Definition ; 6.2. Numerical Results ; CONCLUSION ; REFERENCES ; Chapter 3 FLOAT-ENCODED GENETIC ALGORITHM USED FOR THE INVERSION PROCESSING OF WELL-LOGGING DATA ; ABSTRACT ; 1. INTRODUCTION ; 2. THE INVERSION METHODOLOGY ; 2.1. Forward Modeling ; 2.2. The Inverse Problem ; 2.2.1. Local Inversion Methods ; 2.2.2. Interval Inversion Method ; 3. GENETIC ALGORITHM OPTIMIZATION ; 4. INVERSION EXPERIMENT USING SYNTHETIC DATA ; 5. FIELD CASES.
- 5.1. Application to Water Prospecting 5.2. Application to Hydrocarbon Exploration ; CONCLUSION ; ACKNOWLEDGMENTS ; REFERENCES ; Chapter 4 THE PARTICLE COLLISION ALGORITHM: A METROPOLIS OPTIMIZATION METHOD ; ABSTRACT ; 1. INTRODUCTION ; 2. THE CANONICAL PCA ; Initialization Step ; Main Step ; Exploitation ; Scattering ; 3. APPLICATIONS OF THE PCA IN THE LITERAURE ; 3.1. Nuclear Engineering Problems ; 3.2. Inverse Problems ; 3.3. Course-Timetabling Problems; 4. VARIANTS OF THE PCA; 4.1. Other Local Searching Schemes ; Initialization Step ; Main Step.
- Deterministic Local Search Algorithm (DLSA) Scattering ; 4.2. Multiple-Particle Variants; Initialization Step ; Main Step ; Exploitation ; Scattering ; New Population; Initialization Step ; Main Step ; Exploitation; Scattering ; 4.3. Multi-Neighborhood PCA ; 5. HYBRID APPROACHES; CONCLUSION; ACKNOWLEDGMENTS ; REFERENCES ; Chapter 5 CLASSIFIER-ASSISTED FRAMEWORKS FOR COMPUTATIONALLY EXPENSIVE OPTIMIZATION PROBLEMS; Abstract; 1. Introduction; 2. Background; 2.1. Expensive optimization problems and computational intelligence algorithms; 2.2. Simulator-infeasible vectors; 3. A baseline framework.