Global Optimization Algorithms - Theory and Application

Description

Global Optimization Algorithms - Theory and Application

This e-book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on evolutionary computation by 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 meta-heuristics like simulated annealing, hill climbing, tabu search, and random optimization.

This book addresses two major audience groups:

1. It can help students since we try to describe the algorithms in an understandable, consistent way and, maybe even more important, include all background knowledge needed to understand them. Thus, you can find summaries on stochastic theory and theoretical computer science in part IV on page 349. Additionally, application examples are provided which give an idea how problems can be tackled with the different techniques and what results can be expected.

2. Fellow researchers and PhD students maybe will find the application examples helpful too. For them, in-depth discussions on the single methodologies are included that are supported with a large set of literature references.

_http://www.it-weise.de/projects/

Projects

My research focuses on the application of genetic programming to distributed systems. In the past year I began to develop the Distributed Genetic Programming Framework, a Java system that serves exactly that purpose. Part of this framework was also a suite for evolutionary algorithms, on the genetic programming was based. I have separated this suite from the project in order to separate the different concerns more clearly: now the Standard Interface for Global Optimization Algorithms provides the global optimizers (where genetic programming is a special case of) and the DGPF retains the special genotypes and phenotypes for distributed algorithms functionality.

I want to share the knowledge gathered step by step during my research with others, so I am writing an e-book on the topics of global optimization and genetic programming. This e-book is also intended to relate my practical research (in form of the two Java projects mentioned above) with the theoretical background. It is still work in progress - much is still missing. I will update this book regularly. If you find errors or have further hints what to improve, feel free to contact me - I would be very happy about that.

E-Book "Global Optimization Algorithms - Theory and Application"

At http://www.it-weise.de/projects/book.pdf you can find my e-book "Global Optimization Algorithms". 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. The DGPF and Sigoa projects are based on this book.

Download link: E-Book on Global Optimization Algorithms

Version: 2007-07-18 14:07:47 GMT+0200

Size: 4.681 MiB

Note: The e-book formerly had the title "Global Optimization Techniques and Genetic Programming Applied to Distributed Computing" but it turned out to become more and more comprehensively by time. Finally I decided for a change in title and structure.

http://mihd.net/2dew3q

http://rapidshare.com/files/44213844/global_optimization_algorithms.pdf

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