A Meta-Heuristic Search Algorithm based on Infrasonic Mating Displays in Peafowls

TL;DR

This paper introduces a novel meta-heuristic search algorithm inspired by peafowl mating displays and infrasonic communication, demonstrating competitive performance on benchmark functions compared to existing algorithms.

Contribution

The paper presents a new Infrasonic Search Algorithm inspired by peafowl behavior, expanding the repertoire of bio-inspired meta-heuristics for optimization.

Findings

Outperforms genetic and particle swarm algorithms on benchmark tests

Effective on both unimodal and multimodal functions

Shows promise as a competitive optimization method

Abstract

Meta-heuristic techniques are important as they are used to find solutions to computationally intractable problems. Simplistic methods such as exhaustive search become computationally expensive and unreliable as the solution space for search algorithms increase. As no method is guaranteed to perform better than all others in all classes of optimization search problems, there is a need to constantly find new and/or adapt old search algorithms. This research proposes an Infrasonic Search Algorithm, inspired from the Gravitational Search Algorithm and the mating behaviour in peafowls. The Infrasonic Search Algorithm identified competitive solutions to 23 benchmark unimodal and multimodal test functions compared to the Genetic Algorithm, Particle Swarm Optimization Algorithm and the Gravitational Search Algorithm.