This aggregation is most orbicular improvement algorithms, which are methods to encounter best solutions for presented problems. It especially focuses on evolutionary procedure by discussing evolutionary algorithms, transmitted algorithms, transmitted programming, acquisition classifier systems, phylogenesis strategy, figuring evolution, particle teem optimization, and hymenopteran body optimization.
The aggregation also elaborates on another meta-heuristics, much as simulated annealing, construction climbing, prejudice search, and haphazard optimization.
According to the author, the aggregation is an current impact in advancement that has existed for over digit eld and has been updated and long throughout that time. However, the aggregation module never be ended since there is ever something newborn to add.
Chapters include:
* Evolutionary Algorithms
* Genetic Algorithms
* Genetic Programming
* Evolution Strategy
* Evolutionary Programming
* Learning Classifier Systems
* Hill Climbing
* Random Optimization
* Simulated Annealing
* Tabu Search
* Ant Colony Optimization
* Particle Swarm Optimization
* Memetic Algorithms
* State Space Search
* Parallelization and Distribution
* Maintaining the Optimal Set
* Benchmarks and Toy Problems
* Contests
* Real-World Applications
* Research Applications
* Sigoa - Implementation in Java
* Set Theory
* Stochastic Theory
* Clustering
* Theoretical Computer Science
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