2018  Buch
Practical Mathematical Optimization
Basic Optimization Theory and GradientBased Algorithms
Über dieses Buch
This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradientbased numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradientbased methods. This second edition addresses further advancements of gradientonly optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradientonly solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and directly applicable. Numerical examples and exercises are included to encourage senior to graduatelevel students to plan, execute, and reflect on numerical investigations. By gaining a deep understanding of the conceptual material presented, students, scientists, and engineers will be able to develop systematic and scientific numerical investigative skills.
Inhaltsverzeichnis
Basic optimization theory
Gradientbased algorithms
 Titel
 Practical Mathematical Optimization
 Print ISBN
 9783319775852
 Electronic ISBN
 9783319775869
 CopyrightJahr
 2018
 DOI

https://doi.org/10.1007/9783319775869
 Autoren:

Prof. Jan A Snyman
Daniel N Wilke
BranchenIndex Online
Die B2BFirmensuche für Industrie und Wirtschaft: Kostenfrei in Firmenprofilen nach Lieferanten, Herstellern, Dienstleistern und Händlern recherchieren.
Bildnachweise
Neuer Inhalt/© Stellmach, Neuer Inhalt/© BBL, Neuer Inhalt/© Maturus, Pluta Logo/© Pluta, Neuer Inhalt/© hww, digitale Transformation/© Maksym Yemelyanov  Fotolia