Authors: Amir Hossein Gandomi; Siamak Talatahari; Faraz Tadbiri; Amir Hossein Alavi
Addresses: Department of Civil Engineering, The University of Akron, 244 Sumner St., ASEC 210, Akron, OH 44325-3905, USA ' Marand Faculty of Engineering, University of Tabriz, Tabriz, 51666-14766, Iran ' Department of Structural Engineering, Shabestar Branch, Islamic Azad University, Shabestar, 538165, Iran ' Department of Civil and Environmental Engineering, Engineering Building, Michigan State University, East Lansing, MI 48824, USA
Abstract: Krill herd (KH) algorithm, as a new metaheuristic optimisation, is developed to solve truss optimisation problems. The KH methodology draws its analogy from the herding behaviour of krill individuals in nature. The objective function for the krill movement is mostly influenced by the least distances of each krill individual from food and from highest density of the herd. The new algorithm is examined by solving three truss design optimisation problems and its performance is further compared with various classical and advanced algorithms.
Keywords: metaheuristics; optimum design; truss structures; krill herd algorithm; herding behaviour; bio-inspired computation; truss design; structural design; swarm intelligence.
International Journal of Bio-Inspired Computation, 2013 Vol.5 No.5, pp.281 - 288
Available online: 16 Oct 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article