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Abstract
A new metaheuristic optimization algorithm, called Krill Herd (KH), has been recently proposed by Gandomi and Alavi (2012). In this study, KH is introduced for solving engineering optimization problems. For more verification, KH is applied to six design problems reported in the literature. Further, the performance of the KH algorithm is compared with that of various algorithms representative of the state-of-the-art in the area. The comparisons show that the results obtained by KH are better than the best solutions obtained by the existing methods.
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Notes on contributors
Amir H. Gandomi
Amir H. GANDOMI. He graduated in Civil and Structural Engineering from Iran University of Science & Technology and Tafresh University. He is currently a Researcher in the Department of Civil Engineering at the University of Akron, OH, USA. He is pioneer of Krill Herd algorithm and has published over 100 research papers and book chapters. He has two patents and has published three books in Elsevier. His research interests are intelligent modelling and optimization.
Amir H. Alavi
Amir H. ALAVI. He graduated in Civil and Geotechnical Engineering from Iran University of Science & Technology. He is currently a researcher in Department of Civil & Environmental Engineering at Michigan State University, MI, USA. He is pioneer of Krill Herd algorithm and has published over 100 research papers and book chapters. He has two patents and has published two books in Elsevier. His research interests are civil engineering modelling and optimization.