 Название: Practical Mathematical Optimization
Автор: Jan A Snyman, Daniel N Wilke
Издательство: Springer International Publishing
Год: 2018
Серия: Springer Optimization and Its Applications (Book 133)
ISBN: 9783319775869
Формат: pdf
Страниц: XXVI, 372
Размер: 10,9 mb
Язык: English
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 of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only 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 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.
INTRODUCTION
Snyman, Jan A. (et al.)
Pages 3-40
LINE SEARCH DESCENT METHODS FOR UNCONSTRAINED MINIMIZATION
Snyman, Jan A. (et al.)
Pages 41-69
STANDARD METHODS FOR CONSTRAINED OPTIMIZATION
Snyman, Jan A. (et al.)
Pages 71-112
BASIC EXAMPLE PROBLEMS
Snyman, Jan A. (et al.)
Pages 113-167
SOME BASIC OPTIMIZATION THEOREMS
Snyman, Jan A. (et al.)
Pages 169-193
NEW GRADIENT-BASED TRAJECTORY AND APPROXIMATION METHODS
Snyman, Jan A. (et al.)
Pages 197-250
SURROGATE MODELS
Snyman, Jan A. (et al.)
Pages 251-271
GRADIENT-ONLY SOLUTION STRATEGIES
Snyman, Jan A. (et al.)
Pages 273-310
PRACTICAL COMPUTATIONAL OPTIMIZATION USING PYTHON
Snyman, Jan A. (et al.)
Pages 311-340
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