Advanced Optimization by Nature-Inspired Algorithms

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Bozorg-Haddad, Omid (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Studies in Computational Intelligence, 720
• Θέματα: 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.
• Φυσική περιγραφή: XV, 159 p. 34 illus., 4 illus. in color. online resource.
• ISBN: 9789811052217
• ISSN: 1860-949X ;
• DOI: 10.1007/978-981-10-5221-7

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.