Advanced Optimization by Nature-Inspired Algorithms

• Corporate Author: SpringerLink (Online service)
• Other Authors: Bozorg-Haddad, Omid (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Studies in Computational Intelligence, 720
• Subjects: Computational intelligence.; Mathematical optimization.; Artificial intelligence.; Operations research.; Decision making.; Mechanics.; Mechanics, Applied.; Optical data processing.; Computational Intelligence.; Optimization.; Artificial Intelligence.; Operations Research/Decision Theory.; Theoretical and Applied Mechanics.; Computer Imaging, Vision, Pattern Recognition and Graphics.

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...

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).