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

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.

Use Two Kind Hybridization of the Chaotic Peafowl Algorithm with the Hummingbird Algorithm

“…Where males are distinguished by their long tail compared to females with short or no tail, and their behavior is divided into two parts: social behavior and spatial behavior. [7][8][9][10].…”