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Nature-Inspired Optimization Algorithms - 2nd Edition by Xin-She Yang (Paperback)
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About this item
Highlights
- Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization.
- Author(s): Xin-She Yang
- 310 Pages
- Science, Biotechnology
Description
About the Book
"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"--Book Synopsis
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.- Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature
- Provides a theoretical understanding and practical implementation hints
- Presents a step-by-step introduction to each algorithm
- Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications
Dimensions (Overall): 9.1 Inches (H) x 7.4 Inches (W) x .8 Inches (D)
Weight: 1.2 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 310
Genre: Science
Sub-Genre: Biotechnology
Publisher: Academic Press
Format: Paperback
Author: Xin-She Yang
Language: English
Street Date: September 18, 2020
TCIN: 90762732
UPC: 9780128219867
Item Number (DPCI): 247-12-1873
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 0.8 inches length x 7.4 inches width x 9.1 inches height
Estimated ship weight: 1.2 pounds
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