This paper introduces the Gooseneck Barnacle Optimisation Algorithm (GBO) as a novel
evolutionary method inspired by the natural mating behaviour of gooseneck barnacles …

A new evolutionary algorithm called Barnacles Mating Optimizer (BMO) to solve optimization
problems is presented in this paper. BMO is inspired from the behavior of barnacle'mating in …

In nature, the eastern North American monarch population is known for its southward
migration during the late summer/autumn from the northern USA and southern Canada to …

ABSTRACT The Satin Bowerbird Optimisation (SBO) was inspired by the Satin Bowerbirds
living in Australia's rainforests and other mesic habitats. Like other meta-heuristic algorithms …

Modern optimisation is increasingly relying on meta-heuristic methods. This study presents a
new meta-heuristic optimisation algorithm called Eurasian oystercatcher optimiser (EOO) …

Whale optimization algorithm (WOA) is a newly proposed search optimization technique
which mimics the encircling prey and bubble-net attacking mechanisms of the whale. It has …

In this paper, a novel swarm-based metaheuristic algorithm inspired from the behaviors of
beluga whales, called beluga whale optimization (BWO), is presented to solve optimization …

A population-based optimizer called beluga whale optimization (BWO) depicts behavioral
patterns of water aerobics, foraging, and diving whales. BWO runs effectively, nevertheless it …

As a new and competitive population-based optimization algorithm, the Whale Optimization
Algorithm (WOA) outperforms some other biological-inspired algorithms from the perspective …

This work is a seminal attempt to address the drawbacks of the recently proposed monarch
butterfly optimization (MBO) algorithm. This algorithm suffers from premature convergence …