Coverart for item
The Resource Nature-inspired optimization algorithms, Xin-She Yang, School of Science and Technology, Middlesex University London, London

Nature-inspired optimization algorithms, Xin-She Yang, School of Science and Technology, Middlesex University London, London

Label
Nature-inspired optimization algorithms
Title
Nature-inspired optimization algorithms
Statement of responsibility
Xin-She Yang, School of Science and Technology, Middlesex University London, London
Creator
Author
Subject
Language
eng
Summary
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 and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences . It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference
Cataloging source
BTCTA
http://library.link/vocab/creatorName
Yang, Xin-She
Illustrations
illustrations
Index
no index present
LC call number
QA402.5
LC item number
.Y364 2014
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/subjectName
  • Mathematical optimization
  • Algorithms
  • Algorithms
  • Mathematical optimization
Label
Nature-inspired optimization algorithms, Xin-She Yang, School of Science and Technology, Middlesex University London, London
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
1. Introduction to algorithms -- 2. Analysis of algorithms -- 3. Random walks and optimization -- 4. Simulated annealing -- 5. Genetic algorithms -- 6. Differential evolution -- 7. Particle swarm optimization -- 8. Firefly algorithms -- 9. Cuckoo search -- 10. Bat algorithms -- Flower pollination algorithms -- 12. A framework for self-tuning algorithms -- 13. How to deal with constraints -- 14. Multi-objective optimization -- 15. Other algorithms and hybrid algorithms -- Appendices
Control code
866615538
Dimensions
24 cm
Edition
First edition
Extent
xii, 263 pages
Isbn
9780124167438
Lccn
2014931594
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
(OCoLC)866615538
Label
Nature-inspired optimization algorithms, Xin-She Yang, School of Science and Technology, Middlesex University London, London
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
1. Introduction to algorithms -- 2. Analysis of algorithms -- 3. Random walks and optimization -- 4. Simulated annealing -- 5. Genetic algorithms -- 6. Differential evolution -- 7. Particle swarm optimization -- 8. Firefly algorithms -- 9. Cuckoo search -- 10. Bat algorithms -- Flower pollination algorithms -- 12. A framework for self-tuning algorithms -- 13. How to deal with constraints -- 14. Multi-objective optimization -- 15. Other algorithms and hybrid algorithms -- Appendices
Control code
866615538
Dimensions
24 cm
Edition
First edition
Extent
xii, 263 pages
Isbn
9780124167438
Lccn
2014931594
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
(OCoLC)866615538

Library Locations

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      32.771354 -117.193327
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