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Advanced optimization by nature-insp...

Bozorg-Haddad, Omid.

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Advanced optimization by nature-inspired algorithms

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced optimization by nature-inspired algorithms/ edited by Omid Bozorg-Haddad.
其他作者:	Bozorg-Haddad, Omid.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xv, 159 p. :ill. (some col.), digital ;24 cm.
內容註:	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)
Contained By:	Springer eBooks
標題:	Natural computation. -
電子資源:	http://dx.doi.org/10.1007/978-981-10-5221-7
ISBN:	9789811052217

Advanced optimization by nature-inspired algorithms
Advanced optimization by nature-inspired algorithms[electronic resource] /edited by Omid Bozorg-Haddad. - Singapore :Springer Singapore :2018. - xv, 159 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.7201860-949X ;. - Studies in computational intelligence ;v.720..

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)

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.

ISBN: 9789811052217

Standard No.: 10.1007/978-981-10-5221-7doiSubjects--Topical Terms:

1002233
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Advanced optimization by nature-inspired algorithms
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