Global Optimization Algorithms - Theory and Application

This book elaborates on many of the basic principles in global optimization, evolutionary algorithms, and genetic programming and describes how they can efficiently be realized in software.

**Tag(s):**
Artificial Intelligence

**Publication date**: 11 Jul 2007

**ISBN-10**:
n/a

**ISBN-13**:
n/a

**Paperback**:
n/a

**Views**: 18,222

**Type**: N/A

**Publisher**:
n/a

**License**:
GNU Free Documentation License Version 1.2

**Post time**: 12 Jul 2007 06:05:08

Global Optimization Algorithms - Theory and Application

This book elaborates on many of the basic principles in global optimization, evolutionary algorithms, and genetic programming and describes how they can efficiently be realized in software.

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".

Click**here** to read the full license.

Click

Excerpts from the Preface:

The e-book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on evolutionary computation, discussing evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, differential evolution, particle swarm optimization, and ant colony optimization. It also elaborates on techniques like simulated annealing, hill climbing, tabu search, and random optimization.

The book can help students by also providing the related background in, for example, stochastic and theoretical computer science. Furthermore, application examples as well as a Java implementation of the introduced methods are discussed. The book may however also be interesting for researchers since it also contains in-depth information in many areas and a set of huge literature references.

This book is updated and improved regularly.

The e-book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on evolutionary computation, discussing evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, differential evolution, particle swarm optimization, and ant colony optimization. It also elaborates on techniques like simulated annealing, hill climbing, tabu search, and random optimization.

The book can help students by also providing the related background in, for example, stochastic and theoretical computer science. Furthermore, application examples as well as a Java implementation of the introduced methods are discussed. The book may however also be interesting for researchers since it also contains in-depth information in many areas and a set of huge literature references.

This book is updated and improved regularly.

Tweet

About The Author(s)

Thomas Weise is a computer scientist at the USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI) belonging to the School of Computer Science and Technology (SCST) of the University of Science and Technology of China (USTC). He have worked on research in the field optimization algorithms, mainly centered around Evolutionary Computation.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors