by Thomas Weise, University of Kassel, Distributed Systems Group, July 2007

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.

With this book, we want to address 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.

Download Global Optimization Algorithms - Theory and Application

Pdf format, 4.8mb, 583pages.

Visit Thomas Weise Official Website

Thomas Weise is a computer scientist at University of Kassel.

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