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Here is a free ebook, Global Optimization Algorithms - Theory and Application, which covers 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 other meta-heuristics like Simulated Annealing, hill climbing, TS, and Random Optimization. This algorithm book can help students because the algorithms in an understandable, consistent way and includes much of the background knowledge needed to understand them. Thus, you can find summaries on stochastic theory and theoretical computer science. Also, researchers and PhD students may find the application examples helpful. (652 pages, 9.5mb, pdf format)

Table of Contents:
 - Evolutionary Algorithms
 - Genetic Algorithms
 - Genetic Programming
 - Learning Classifier Systems
 - Hill Climbing
 - Simulated Annealing
 - Example Applications
 - Sigoa – Implementation in Java
 - Background (Mathematics, Computer Science)

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