Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

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 …

This study presents the analysis and principle of an innovative optimizer named weIghted
meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

This work presents a novel nature-inspired metaheuristic called Nutcracker Optimization
Algorithm (NOA) inspired by Clark's nutcrackers. The nutcrackers exhibit two distinct …

The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers.
Most of these cliché methods mimic animals' searching trends and possess a small …

This paper proposes a novel swarm intelligence-based metaheuristic called as sea-horse
optimizer (SHO), which is inspired by the movement, predation and breeding behaviors of …

Meta-heuristic algorithms are becoming more prevalent and have been widely applied in
various fields. There are numerous reasons for the success of such techniques in both …

Numerous optimization problems can be addressed using metaheuristics instead of
deterministic and heuristic approaches. This study proposes a novel population-based …