In this work, a novel binary version of the grey wolf optimization (GWO) is proposed and used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the latest bioinspired optimization techniques, which simulate the hunting process of grey wolves in nature. The binary version introduced here is performed using two different approaches. In the first app...

Abstract A grey wolf optimization algorithm based on an adaptive adjustment strategy (Improvements-Grey Wolf Optimization, IGWO) is proposed in this paper to address the issues with Grey Optimization (GWO) algorithm, which has a slow convergence speed later stages and where local search global cannot be taken into effective balance. First, chaotic logistic map used initialize population. Next, ...