Search and Optimization by Metaheuristics
Techniques and Algorithms Inspired by Nature
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ISBN-13:
9783319822907
Veröffentl:
2018
Einband:
Paperback
Erscheinungsdatum:
31.05.2018
Seiten:
456
Autor:
M. N. S. Swamy
Gewicht:
686 g
Format:
235x155x25 mm
Sprache:
Englisch
Beschreibung:
This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones.
Offers a comprehensive and state-of-the-art introduction to nature-inspired metaheuristics
Preface.- Introduction.- Simulated Annealing.- Optimization by Recurrent Neural Networks.- Genetic Algorithms and Genetic Programming.- Evolutionary Strategies.- Differential Evolution.- Estimation of Distribution Algorithms.- Mimetic Algorithms.- Topics in EAs.- Particle Swarm Optimization.- Artificial Immune Systems.- Ant Colony Optimization.- Tabu Search and Scatter Search.- Bee Metaheuristics.- Harmony Search.- Biomolecular Computing.- Quantum Computing.- Other Heuristics-Inspired Optimization Methods.- Dynamic, Multimodal, and Constraint-Satisfaction Optimizations.- Multiobjective Optimization.- Appendix 1: Discrete Benchmark Functions.- Appendix 2: Test Functions.- Index.
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