Fundamentals of Optimization Techniques with Algorithms

Fundamentals of Optimization Techniques with Algorithms
Author :
Publisher : Academic Press
Total Pages : 323
Release :
ISBN-10 : 9780128224922
ISBN-13 : 0128224924
Rating : 4/5 (924 Downloads)

Book Synopsis Fundamentals of Optimization Techniques with Algorithms by : Sukanta Nayak

Download or read book Fundamentals of Optimization Techniques with Algorithms written by Sukanta Nayak and published by Academic Press. This book was released on 2020-08-25 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLABĀ© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice. Presents optimization techniques clearly, including worked-out examples, from traditional to advanced Maps out the relations between optimization and other mathematical topics and disciplines Provides systematic coverage of algorithms to facilitate computer coding Gives MATLABĀ© codes in relation to optimization techniques and their use in computer-aided design Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks


Fundamentals of Optimization Techniques with Algorithms Related Books

Fundamentals of Optimization Techniques with Algorithms
Language: en
Pages: 323
Authors: Sukanta Nayak
Categories: Technology & Engineering
Type: BOOK - Published: 2020-08-25 - Publisher: Academic Press

DOWNLOAD EBOOK

Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral rol
Optimization Techniques and Applications with Examples
Language: en
Pages: 384
Authors: Xin-She Yang
Categories: Mathematics
Type: BOOK - Published: 2018-09-19 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and c
Optimization in Engineering
Language: en
Pages: 412
Authors: Ramteen Sioshansi
Categories: Mathematics
Type: BOOK - Published: 2017-06-24 - Publisher: Springer

DOWNLOAD EBOOK

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engi
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
Optimization for Data Analysis
Language: en
Pages: 239
Authors: Stephen J. Wright
Categories: Computers
Type: BOOK - Published: 2022-04-21 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.