_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.
* Discusses and summarizes the latest developments in nature-inspired
algorithms with comprehensive, timely literature
* Provides a theoretical understanding as well as practical
implementation hints
* Provides a step-by-step introduction to each algorithm
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Produktdetaljer
ISBN
9780124167438
Publisert
2014
Utgiver
Vendor
Elsevier (S&T)
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter