Teaching-learning-based optimization (TLBO) is an optimization algorithm that has become
very popular in recent years and has shown excellent performance in solving many scientific …

Background Improvement on the updating equation of an algorithm is among the most
improving techniques. Due to the lack of search ability, high computational complexity and …

In this paper, an optimization algorithm called supercell thunderstorm algorithm (STA) is
proposed. STA draws inspiration from the strategies employed by storms, such as spiral …

This paper summarizes the community where people live development laws and proposes a
novel meta-heuristic called community development algorithm (CDA). To enhance the …

As stated in the no-free-lunch (NFL) theory, there is not any optimizer suitable for all
problems. This circumstance becomes the motivation of introducing a new swarm-based …

Optimal reactive power dispatch (ORPD) problems are important tools for the sake of
security and economics of power systems. The ORPD problems are nonlinear optimization …

Traditional population-based metaheuristic algorithms are effective in solving complex real-
world problems but require careful strategy selection and parameter tuning. Metaphorless …

In the recent years, there are a lot of swarm-based stochastic optimization techniques ie,
metaheuristics were introduced. Most of these techniques were tested to solve the sets of …

In the navigation of unmanned surface vehicles (USVs), various types of obstacles may be
encountered, which can be categorized into real-time collision avoidance among multiple …

This paper introduces a novel metaheuristic named the stochastic shaking algorithm (SSA),
which is rooted in swarm intelligence principles. The innovation lies in its unique utilization …