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Practical Mathematical Optimization : An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms
This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form without neglecting rigour. The work should enable the professional to apply optimization theory and algorithms to his own particular practical field of interest, be it engineering, physics, chemistry, or business economics. Most importantly, for the first time in a relatively brief and introductory work, due attention is paid to the difficulties—such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima—that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers.
Optimisation in Computational Fluid Dynamics
The numerical optimization of practical applications is an issue of growing importance in research and industry. It allows both the exploration of non-trivial configurations differing widely from all known solutions and the step-by-step improvement of existing designs.The purpose of this book is to introduce the state of the art concerning this issue, referred to in the book as CFD-based Optimization (CFD-O). Many complementary applications are presented, so that interested researchers and engineers will get a clear view of the present possibilities for all problems where the numerical optimization process relies on evaluations obtained through Computational Fluid Dynamics.
