The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

This study tenders a new nature-inspired metaheuristic algorithm (MA) based on the
behavior of the Genghis Khan shark (GKS), called GKS optimizer (GKSO), which is used for …

The development of efficient optimization algorithms is crucial across various scientific
disciplines. As the complexity and diversity of optimization problems continue to grow …

Achieving sustainable development goals requires integrating renewable energy systems
(RESs) into our current energy infrastructure. However, sophisticated approaches are …

This study presents a powerful and new modeling variant of bio-inspired algorithms, namely,
the Ivy algorithm (IVYA), drawn from the growth patterns of Ivy plants. The algorithm …

Introducing a novel meta-heuristic optimization algorithm, the Flood Algorithm (FLA) draws
inspiration from the intricate movement and flow patterns of water masses during flooding …

This paper introduces the Botox Optimization Algorithm (BOA), a novel metaheuristic
inspired by the Botox operation mechanism. The algorithm is designed to address …

This study introduces an enhanced self-adaptive wild goose algorithm (SAWGA) for solving
economical-environmental-technical optimal power flow (OPF) problems in traditional and …

In modern warfare, unmanned aerial vehicles (UAVs) have become a vital military force.
Planning feasible paths for UAVs has become an essential part of forming autonomous …

Energy management in power grids becomes essential to reduce the cost for the consumer
and improve the power supply reliability. The microgrid is a vital part of the smart grid and it …