Harmony Search Algorithm

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ISBN/EAN: 9783662479261

The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community.  This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields.

Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications. The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques.

This book offers a valuable snapshot of the current status of the Harmony Search Algorithm and related techniques, and will be a useful reference for practising researchers and advanced students in computer science and engineering.



Dr. Joong Hoon Kim is a professor at the School of Civil, Environmental, and Architectural Engineering, Korea University since March 1993. He has earned the B.E. degree in Civil Engineering from Korea University in 1984. He received an M.S.C.E. from Virginia Polytechnic Institute and State University in 1986 and the Doctor of Philosophy from the University of Texas at Austin in 1992. He worked as a faculty associate at Arizona State University from August 1989 to July 1990. He also worked at the Flood Control District of Maricopa County, Arizona, USA, as a branch manager from January 1991 to February 1993. He was Chair of School of Civil, Environmental and Architectural Engineering, Korea University for four years.

Professor Kim is currently managing several government projects including research of 'Establishment of Original Technology and Globalization Strategy of Harmony Search Algorithm' funded by National Research Foundation of Korea, and 'Technology to Improve Urban Disaster Prevention Performance for Flood Proofing Facilities and Development of Optimal Design & Operation system for Urban drainage network' funded by Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Dr. Zong Woo Geem is an assistant professor at Gachon University in South Korea. He has obtained B.S. degree in Chung-Ang University in Civil Engineering (1991), Master of Engineering (1995) and Ph.D. (2000) in Water Resources Engineering at Korea University. He invented a music-inspired optimization algorithm, Harmony Search, which has been applied to various scientific and engineering problems, for his Ph.D. dissertation under supervision of Prof. Joong Hoon Kim. He served as an academic advisor in iGlobal University at Annandale, Virginia, USA.

Professor Geem is currently an associate editor of engineering optimization journal and a guest editor of International Journal of Bio-Inspired Computation and

Journal of Applied Mathematics. Besides, he is a member of editorial board of International Journal of Mathematical Modelling and Numerical Optimization. Professor Geem is active reviewer for 74 journals including SCIe journals.

His research interest includes phenomenon-mimicking algorithm and its applications to energy, environment and water fields, and water distribution systems. He has published more than 90 papers in SCI, and SCIe and domestic journals.

Autor: Joong Hoon Kim, Zong Woo Geem
EAN: 9783662479261
eBook Format: PDF
Sprache: Englisch
Produktart: eBook
Veröffentlichungsdatum: 08.08.2015
Untertitel: Proceedings of the 2nd International Conference on Harmony Search Algorithm (ICHSA2015)
Kategorie:
Schlagworte: Ant Colony Optimization Cuckoo Search Evolutionary computing Strategies Firefly Algorithm Genetic Algorithm Harmony Search Algorithm (HSA) Hybrid and multi-objective HSA variants ICHSA 2015 Proceedings Particle Swarm Optimization Simulated A

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