Essentials of Metaheuristics

Essentials of Metaheuristics

4.44 (18 ratings by Goodreads)
  • Paperback
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Description

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 70 figures and 133 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, and XCS.
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Product details

  • Paperback | 230 pages
  • 214 x 276 x 20mm | 639.56g
  • London, United Kingdom
  • 0557148596
  • 9780557148592

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18 ratings
4.44 out of 5 stars
5 56% (10)
4 33% (6)
3 11% (2)
2 0% (0)
1 0% (0)
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