Whale swarm algorithm for function optimization

TL;DR

This paper introduces the Whale Swarm Algorithm, a new nature-inspired metaheuristic based on whale communication, demonstrating competitive performance in function optimization tasks compared to existing algorithms.

Contribution

The paper presents a novel Whale Swarm Algorithm inspired by whale communication, expanding the toolkit of nature-inspired metaheuristics for optimization.

Findings

Whale Swarm Algorithm performs competitively on benchmark problems.

The algorithm effectively mimics whale ultrasound communication.

Experimental results show it outperforms some existing metaheuristics.

Abstract

Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is inspired by the whales behavior of communicating with each other via ultrasound for hunting. The proposed Whale Swarm Algorithm has been compared with several popular metaheuristic algorithms on comprehensive performance metrics. According to the experimental results, Whale Swarm Algorithm has a quite competitive performance when compared with other algorithms.