Global Optimization Algorithms - Theory and Application
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|Home page, featuring an e-book (PDF format, approximately 10MB) devoted to global optimization algorithms, which are methods of finding 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 is work in progress, updated often. Check back for the latest revisions.|
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