Advanced Optimization by Nature-Inspired Algorithms
Title:
Advanced Optimization by Nature-Inspired Algorithms
Author:
Bozorg-Haddad, Omid. editor.
ISBN:
9789811052217
Physical Description:
XV, 159 p. 34 illus., 4 illus. in color. online resource.
Series:
Studies in Computational Intelligence, 720
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).
Abstract:
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 addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.
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Electronic Access:
https://doi.org/10.1007/978-981-10-5221-7