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Nature-inspired optimization algorithms
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-ch...
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| Lenguaje: | eng |
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Elsevier Science
2014
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| Acceso en línea: | http://cds.cern.ch/record/1668173 |
| _version_ | 1780935475334217728 |
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| author | Yang, Xin-She |
| author_facet | Yang, Xin-She |
| author_sort | Yang, Xin-She |
| collection | CERN |
| description | Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning |
| id | cern-1668173 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2014 |
| publisher | Elsevier Science |
| record_format | invenio |
| spelling | cern-16681732021-04-21T21:14:51Zhttp://cds.cern.ch/record/1668173engYang, Xin-SheNature-inspired optimization algorithmsComputing and Computers Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning Elsevier Scienceoai:cds.cern.ch:16681732014 |
| spellingShingle | Computing and Computers Yang, Xin-She Nature-inspired optimization algorithms |
| title | Nature-inspired optimization algorithms |
| title_full | Nature-inspired optimization algorithms |
| title_fullStr | Nature-inspired optimization algorithms |
| title_full_unstemmed | Nature-inspired optimization algorithms |
| title_short | Nature-inspired optimization algorithms |
| title_sort | nature-inspired optimization algorithms |
| topic | Computing and Computers |
| url | http://cds.cern.ch/record/1668173 |
| work_keys_str_mv | AT yangxinshe natureinspiredoptimizationalgorithms |