New inspirations in swarm intelligence: a survey

TLDR

The increasing complexity of real‑world problems has driven computer scientists to seek efficient solutions, leading to swarm intelligence meta‑heuristics inspired by diverse natural behaviours such as bees, bacteria, and fireflies. The tutorial surveys recent nature‑inspired metaphors used in swarm intelligence meta‑heuristics. The authors describe the biological behaviours that underpin the development of various computational algorithms. The survey reports recent applications and key features of these meta‑heuristics.

Abstract

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary computation and swarm intelligence meta-heuristics are outstanding examples that nature has been an unending source of inspiration. The behaviour of bees, bacteria, glow-worms, fireflies, slime moulds, cockroaches, mosquitoes and other organisms have inspired swarm intelligence researchers to devise new optimisation algorithms. This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence meta-heuristics. We describe the biological behaviours from which a number of computational algorithms were developed. Also, the most recent and important applications and the main features of such meta-heuristics are reported.