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.

This text covers numerical methods and optimization and has an abundance of practical application Exercises of varying level of difficulty give new examples and ideas for exam/homework problems Accessible to students and engineers with some background in linear algebra and calculus

Autorentext

Jean-Pierre Corriou is Emeritus Professor of the University of Lorraine. He performs his research in the research group of Dynamic Optimization and Advanced Control of the Laboratory of Reactions and Chemical Engineering (LRGP). Prof. Corriou's main research domains include dynamic simulation of complex processes and nonlinear control of processes. In addition to this present text, Prof. Corriou has published 2 editions of a textbook with Springer titled "Process Control --- Theory and Applications."

Inhalt
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.