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...

Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on complex-valued encoding; namely the complex-valued encoding grey wolf optimization (CGWO). We use CGWO to test 16 u...

In the recent years, the optimization techniques using evolutionary algorithms have been widely used to solve electromagnetic problems. These algorithms use thinning the antenna arrays with the aim of reducing the complexity and thus achieving the optimal solution and decreasing the side lobe level. To obtain the optimal solution, thinning is performed by removing some elements in an array thro...

Nature has always been a source of inspiration for solving complex engineering problems. It could be easily observed in the latest optimization algorithms that have been inspired by nature. Grey Wolf Optimization algorithm is a recent optimization algorithm that has been inspired by hunting behavior of grey wolves. In this paper, this algorithm has been investigated for the process of software ...

The grey wolf optimization (GWO) is a nature inspired and meta-heuristic algorithm, it has successfully solved many problems give better solution as compare to other algorithms. However, due its poor exploration capability, imbalance relation between exploitation. Therefore, in this research work, the part of GWO was improved through hybrid with whale algorithm (WOA) exploration. proposed (GWWO...

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, ...