Swarm Optimization

Swarm optimization is a computational intelligence field focused on developing algorithms inspired by the collective behavior of social insects, animals, or other natural swarms to solve complex optimization problems. Current research emphasizes the development and refinement of novel swarm algorithms, such as those based on rat, cat, scorpion, shrike, egret, and duck behaviors, often incorporating modifications to improve exploration-exploitation balance and convergence speed. These algorithms find applications in diverse fields, including engineering design, cybersecurity (APT detection), and feature selection, demonstrating their effectiveness in tackling challenging real-world optimization tasks. The ongoing development and rigorous benchmarking of these algorithms contribute significantly to the advancement of optimization techniques across various scientific and engineering disciplines.