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 other metaheuristics like Simulated Annealing, Extremal Optimization, Tabu Search, and Random Optimization. The book is no book in the conventional sense: Because of frequent updates and changes, it is not really intended for sequential reading but more as some sort of material collection, encyclopedia, or reference work where you can look up stuff, find the correct context, and are provided with fundamentals.

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Global Optimization Algorithms
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Last Update: May 14, 2024
Relased: May 14, 2024

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