This textbook is designed for students and industry practitioners for a first course in optimization integrating MATLAB(R) software.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr Achille Messac received his B.S., M.S., and Ph.D. from MIT in Aerospace Engineering. Dr Messac is a Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and the American Society of Mechanical Engineers. He has authored or co-authored over 70 journal and 130 conference articles, chaired several international conferences, delivered several keynote addresses, and received the prestigious AIAA Multidisciplinary Design Optimization Award. He has taught or advised undergraduate and graduate students in the areas of design and optimization for over three decades at Rensselaer Polytechnic Institute, MIT, Syracuse University, Mississippi State and Northeastern University.
Inhaltsangabe
Part I. Helpful Preliminaries: 1. MATLAB® as a computational tool 2. Mathematical preliminaries Part II. Using Optimization - the Road Map: 3. Welcome to the fascinating world of optimization 4. Analysis, design, optimization, and modeling 5. Introducing linear and nonlinear programming Part III. Using Optimization - Practical Essentials: 6. Multiobjective optimization 7. Numerical essentials 8. Global optimization basics 9. Discrete optimization basics 10. Practicing optimization - larger examples Part IV. Going Deeper: Inside the Codes and Theoretical Aspects: 11. Linear programming 12. Nonlinear programming with no constraints 13. Nonlinear programming with constraints Part V. More Advanced Topics in Optimization: 14. Discrete optimization 15. Modeling complex systems: surrogate modeling and design space reduction 16. Design optimization under uncertainty 17. Methods for Pareto frontier generation/representation 18. Physical programming for multiobjective optimization 19. Evolutionary algorithms.
Part I. Helpful Preliminaries: 1. MATLAB® as a computational tool 2. Mathematical preliminaries Part II. Using Optimization - the Road Map: 3. Welcome to the fascinating world of optimization 4. Analysis, design, optimization, and modeling 5. Introducing linear and nonlinear programming Part III. Using Optimization - Practical Essentials: 6. Multiobjective optimization 7. Numerical essentials 8. Global optimization basics 9. Discrete optimization basics 10. Practicing optimization - larger examples Part IV. Going Deeper: Inside the Codes and Theoretical Aspects: 11. Linear programming 12. Nonlinear programming with no constraints 13. Nonlinear programming with constraints Part V. More Advanced Topics in Optimization: 14. Discrete optimization 15. Modeling complex systems: surrogate modeling and design space reduction 16. Design optimization under uncertainty 17. Methods for Pareto frontier generation/representation 18. Physical programming for multiobjective optimization 19. Evolutionary algorithms.
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