Editors:
- Collects a wide range of the most important algorithms which are useful in engineering
- Provides a step-by-step presentation of each algorithm with guidelines for coding algorithms
- Also provides a theoretical understanding as well as guidelines for practical implementation
- Describes all the algorithms with similar attention to detail, thus facilitating their reading and learning
- Relates the optimization algorithms to engineering optimization problems
- Facilitates rapid and effective learning
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 720)
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Table of contents (15 chapters)
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Front Matter
About this book
Keywords
- Pattern Search (PS) Algorithm
- Genetic Algorithm (GA)
- Simulated Annealing (SA)
- Tabu Search Algorithm (TSA)
- Ant Colony Optimization (ACO)
- Particle Swarm Optimization (PSO)
- Differential Evolution (DE)
- Harmony Search (HS)
- Shuffled Frog-Leaping Algorithm (SFLA)
- Honey-Bee Mating Optimization (HBMO)
- Invasive Weed Optimization (IWO)
- Central Force Optimization (CFO)
- Biogeography-Based Optimization (BBO)
- Firefly Algorithm (FA)
- Gravity Search Algorithm (GSA)
- Bat Algorithm (BA)
- Plant Propagation Algorithm (PPA)
- Water Cycle Algorithm (WCA)
- Symbiotic Organisms Search (SOS) Algorithm
- Comprehensive Evolutionary Algorithm (CEA)
Editors and Affiliations
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Irrigation & Reclamation Engineering, University of Tehran College of Agriculture & Natural Resources, Karaj, Iran
Omid Bozorg-Haddad
About the editor
Prof. Hugo Loaiciga served as the Water Commissioner for the City of Santa Barbara for six years before joining the Department in 1988. He received the 2002 Service to the Profession Award from the American Society of Civil Engineers and the Environmental and Water Resources Institute for his "longstanding contributions to research and technical activities" of the two groups, and he was elected a Fellow of the American Society of Civil Engineers for his "outstanding contributions to the planning, analysis, and operation of water resources engineering" in 2007.
Bibliographic Information
Book Title: Advanced Optimization by Nature-Inspired Algorithms
Editors: Omid Bozorg-Haddad
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-981-10-5221-7
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2018
Hardcover ISBN: 978-981-10-5220-0Published: 11 July 2017
Softcover ISBN: 978-981-13-5345-1Published: 23 December 2018
eBook ISBN: 978-981-10-5221-7Published: 30 June 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XV, 159
Number of Illustrations: 30 b/w illustrations, 4 illustrations in colour
Topics: Computational Intelligence, Optimization, Artificial Intelligence, Operations Research/Decision Theory, Theoretical and Applied Mechanics, Computer Imaging, Vision, Pattern Recognition and Graphics