metaheuristicOpt

An implementation of metaheuristic algorithms for continuous optimization. Currently, the package contains the implementations of 21 algorithms, as follows: particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, 2015 [doi:10.1016/j.advengsoft.2015.01.010]), grey wolf optimizer (Mirjalili et al., 2014 [doi:10.1016/j.advengsoft.2013.12.007]), dragonfly algorithm (Mirjalili, 2015 [doi:10.1007/s00521-015-1920-1]), firefly algorithm (Yang, 2009 [doi:10.1007/978-3-642-04944-6_14]), genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation algorithm (Saremi et al., 2017 [doi:10.1016/j.advengsoft.2017.01.004]), harmony search algorithm (Mahdavi et al., 2007 [doi:10.1016/j.amc.2006.11.033]), moth flame optimizer (Mirjalili, 2015 [doi:10.1016/j.knosys.2015.07.006]), sine cosine algorithm (Mirjalili, 2016 [doi:10.1016/j.knosys.2015.12.022]), whale optimization algorithm (Mirjalili and Lewis, 2016 [doi:10.1016/j.advengsoft.2016.01.008]), clonal selection algorithm (Castro, 2002 [doi:10.1109/TEVC.2002.1011539]), differential evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).

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