BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms
Stock photo: cover may vary

Nature-Inspired Optimization Algorithms Papeback -

by Xin-She Yang

Add to wish list
  • New
New

Description

Elsevier , pp. 332 . Papeback. New.
Ask the seller a question Add to wish list
A$259.96
A$5.77 Delivery within USA
Standard delivery: 9 to 14 days
More delivery options
Ships from Cold Books (New York, United States)

Details

  • Title Nature-Inspired Optimization Algorithms
  • Author Xin-She Yang
  • Binding Papeback
  • Condition New
  • Pages 310
  • Volumes 1
  • Language ENG
  • Publisher Elsevier
  • Publication date pp. 332
  • Features Bibliography, Index
  • Bookseller's Inventory # 6377007934
  • ISBN 9780128219867 / 0128219866
  • Weight 1.2 lbs (0.54 kg)
  • Dimensions 9.1 x 7.4 x 0.8 in (23.11 x 18.80 x 2.03 cm)
  • Category Science
  • Library of Congress subjects Mathematical optimization, Nature-inspired algorithms
  • Library of Congress Catalogue Number 2020951293
  • Quantity available 3

About Cold Books New York, United States

Biblio member since 2012

Terms of Sale: 30 day return guarantee, with full refund including shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Cold Books

Reader reviews for Nature-Inspired Optimization Algorithms

From the publisher

Nature-Inspired Optimization Algorithms, Second Edition provides an 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 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, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications.
tracking-