عنوان

Algorithms for optimization /

شابک

0262039427

شابک

9780262039420

عنوان اصلي

Algorithms for optimization /

نام عام مواد

[Book]

نام نخستين پديدآور

Mykel J. Kochenderfer, Tim A. Wheeler.

محل نشرو پخش و غیره

Cambridge, Massachusetts :

نام ناشر، پخش کننده و غيره

The MIT Press,

تاریخ نشرو بخش و غیره

[2019]

تاریخ نشرو بخش و غیره

©2019

نام خاص و کميت اثر

xx, 500 pages :

ساير جزييات

illustrations (some color) ;

ابعاد

24 cm

متن يادداشت

Includes bibliographical references (pages 483-493) and index.

متن يادداشت

Preface -- Acknowledgments - Introduction -- 2 Derivatives and Gradients -- Bracketing -- Local Descent -- First-Order Methods -- Second-Order Methods -- Direct Methods -- Stochastic Methods -- Population Methods - Constraints -- Linear Constrained Optimization -- Multiobjective Optimization -- Sampling Plans -- Surrogate Models -- Probabilistic Surrogate Models -- Surrogate Optimization -- Optimization under Uncertainty -- Uncertainty Propagation -- Discrete Optimization -- Expression Optimization -- Multidisciplinary Optimization - Julia -- Test Functions -- Mathematical Concepts -- Solutions -- Bibliography -- Index

بدون عنوان

0

متن يادداشت

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals. -- Provided by publisher.

موضوع مستند نشده

Algorithms, Problems, exercises, etc.

موضوع مستند نشده

Algorithms.

موضوع مستند نشده

Mathematical optimization.

موضوع مستند نشده

Algorithms.

موضوع مستند نشده

Algorithmus

موضوع مستند نشده

Mathematical optimization.

شماره

ويراست

شماره رده

شماره رده

نشانه اثر

نشانه اثر

مستند نام اشخاص تاييد نشده

Kochenderfer, Mykel J.,1980-

مستند نام اشخاص تاييد نشده

Wheeler, Tim A., (Tim Allan)

تاريخ عمليات

20200822104755.0

قواعد فهرست نويسي ( بخش توصيفي )

rda

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y