Advanced Optimization by Nature-Inspired Algorithms

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In a...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Bozorg-Haddad, Omid (Editor)
Format: e-Book
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Studies in Computational Intelligence, 720
Subjects:
Computational intelligence.
Mathematical optimization.
Artificial intelligence.
Operations research.
Mechanics, Applied.
Image processing > Digital techniques.
Computer vision.
Computational Intelligence.
Optimization.
Artificial Intelligence.
Operations Research and Decision Theory.
Engineering Mechanics.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Online Access:Full-text access
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Table of Contents:
  • Introduction
  • Cat Swarm Optimization (CSO) Algorithm
  • League Championship Algorithm (LCA)
  • Anarchic Society Optimization (ASO) Algorithm
  • Cuckoo Optimization Algorithm (COA)
  • Teaching-Learning-Based Optimization (TLBO) Algorithm
  • Flower pollination Algorithm (FPA)
  • Krill Herd Algorithm (KHA)
  • Grey Wolf Optimization (GWO) Algorithm
  • Shark Smell Optimization (SSO) Algorithm
  • Ant Lion Optimizer (ALO) Algorithm
  • Gradient Evolution (GE) Algorithm
  • Moth-Flame Optimization (MFO) Algorithm
  • Crow Search Algorithm (CSA)
  • Dragonfly Algorithm (DA).

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