Algorithms for Optimization

Algorithms for Optimization
Author :
Publisher : MIT Press
Total Pages : 521
Release :
ISBN-10 : 9780262039420
ISBN-13 : 0262039427
Rating : 4/5 (20 Downloads)

Book Synopsis Algorithms for Optimization by : Mykel J. Kochenderfer

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Algorithms for Optimization Related Books

Algorithms for Optimization
Language: en
Pages: 521
Authors: Mykel J. Kochenderfer
Categories: Computers
Type: BOOK - Published: 2019-03-12 - Publisher: MIT Press

DOWNLOAD EBOOK

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introd
Optimal Algorithms
Language: en
Pages: 324
Authors: Hristo Djidjev
Categories: Computers
Type: BOOK - Published: 1989-11-08 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This volume brings together papers from various fields of theoretical computer science, including computational geometry, parallel algorithms, algorithms on gra
Optimal Quadratic Programming Algorithms
Language: en
Pages: 293
Authors: Zdenek Dostál
Categories: Mathematics
Type: BOOK - Published: 2009-04-03 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Quadratic programming (QP) is one advanced mathematical technique that allows for the optimization of a quadratic function in several variables in the presence
Elements of the General Theory of Optimal Algorithms
Language: en
Pages: 387
Authors: Ivan V. Sergienko
Categories: Mathematics
Type: BOOK - Published: 2022-01-11 - Publisher: Springer Nature

DOWNLOAD EBOOK

In this monograph, the authors develop a methodology that allows one to construct and substantiate optimal and suboptimal algorithms to solve problems in comput
Evolutionary Optimization Algorithms
Language: en
Pages: 776
Authors: Dan Simon
Categories: Mathematics
Type: BOOK - Published: 2013-06-13 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs