Optimization problems arise in diverse fields such as engineering, economics, and industry.
Metaheuristic algorithms, including the Simulated Kalman Filter (SKF), have been …

This study introduces a new single-agent metaheuristic algorithm, named cubature Kalman
optimizer (CKO). The CKO is inspired by the estimation ability of the cubature Kalman filter …

Simulated Kalman filter (SKF) is a new population-based optimization algorithm inspired by
estimation capability of Kalman filter. Each agent in SKF is regarded as a Kalman filter …

Abstract The Grey Wolf Optimizer (GWO) is a relatively new metaheuristic approach that has
shown promising results in solving continuous optimization problems. The Grey Wolf …

Metaheuristics algorithms solve optimization problems by repeating a set of procedures. The
algorithms can be categorized based on number of agents, either single agent algorithms …

Abstract Asynchronous Finite Impulse Response Optimizer (AFIRO) is a metaheuristic
algorithm that has been developed as a population-based solution with an asynchronous …

Abstract The original Simulated Kalman Filter (SKF) is an optimizer that employs
synchronous update mechanism. The agents in SKF update their solutions after all fitness …

Optimization problems are frequently found in various fields. The classification of estimation-
based metaheuristic algorithms has been introduced for solving optimization problems …

With the improvement of living standards and the popularity of computer, web and camera
applications, people can easily capture many image and video footage and applications …