Interested in the Genetic Algorithm? Simulated Annealing? Ant
Colony Optimization? Essentials of Metaheuristics covers these and
other metaheuristics algorithms, and is intended for undergraduate
students, programmers, and non-experts. The book covers a wide
range of algorithms, representations, selection and modification
operators, and related topics, and includes 71 figures and 135
algorithms great and small. Algorithms include: Gradient Ascent
techniques, Hill-Climbing variants, Simulated Annealing, Tabu
Search variants, Iterated Local Search, Evolution Strategies, the
Genetic Algorithm, the Steady-State Genetic Algorithm, Differential
Evolution, Particle Swarm Optimization, Genetic Programming
variants, One- and Two-Population Competitive Coevolution,
N-Population Cooperative Coevolution, Implicit Fitness Sharing,
Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony
Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA,
BOA, SAMUEL, ZCS, XCS, and XCSF.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!