9783319775852 - Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms (Springer Optimization and Its Applications, 133, Band 133) von Snyman (6 Ergebnisse)

Hardcover. Zustand: Very Good. 2nd ed. 2018. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Original-Pappband. Zustand: Sehr gut. gr8 Original-Pappband 2nd Ed. en (Springer Optimization and Its Applications, Vol. 133) XXVI, 372 pp.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 gradient-based 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 gradient-based methods. This second edition addresses further advancements ofgradient-only optimization strategies to handlediscontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies andnumerical optimizationusing 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 graduate-level 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.