From the solitudinarian era to the present, the human race has been striving towards the
betterment of his life by trying to find out the hidden secrets of our nature. Some time back …

In this article, an Improved Grey Wolf Optimizer (I-GWO) is proposed for solving global
optimization and engineering design problems. This improvement is proposed to alleviate …

Automatic path planning problem is essential for efficient mission execution by unmanned
aerial vehicles (UAVs), which needs to access the optimal path rapidly in the complicated …

Autonomous navigation is significant to UAVs, especially in disaster scenarios. A Hybrid
GWO and Differential Evolution (HGWODE) algorithm is developed to solve UAV path …

Differential evolution is an effective and practical approach that is widely applied for solving
global optimization problems. Nevertheless, its effectiveness and scalability are decreased …

Path planning is one of the most important steps in the navigation and control of Unmanned
Aerial Vehicles (UAVs). It ensures an optimal and collision-free path between two locations …

DE algorithms have outstanding performance in solving complex problems. However, they
also have highlighted the need for an effective approach to alleviating the risk of premature …

Quickly, accurately and reliably extract the parameters of solar photovoltaic (PV) model is
very critical to simulate, evaluate and control the PV systems. During the past few years …

In this article, an effective metaheuristic algorithm named multi-trial vector-based differential
evolution (MTDE) is proposed. The MTDE is distinguished by introducing an adaptive …

In this article, an improved variant of the grey wolf optimizer (GWO) named gaze cues
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …