Προσθήκη στα αγαπημένα
This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in Matlab™ is available on the author’s personal website and presents both numerical and optimization methods.
Preface.-Nomenclature.- 1. Interpolation and Approximation.- 2. Numerical Integration.- 3. Equation Solving by Iterative Methods.- 4. Numerical Operations on Matrices.- 5. Numerical Solution of Systems of Algebraic Equations.- 6. Numerical Integration of Ordinary Differential Equations.- 7. Numerical Integration of Partial Differential Equations.- 8. Analytical Methods for Optimization.- 9. Numerical Methods of Optimization.- 10. Linear Programming.- 11. Quadratic Programming and Nonlinear Optimization.- 12. Dynamic optimization.- Index.
Περιγραφή
This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in Matlab™ is available on the author’s personal website and presents both numerical and optimization methods.
