Title: A comprehensive review on recent intelligent metaheuristic algorithms

Authors: S. Rajalakshmi; S. Kanmani

Addresses: Pondicherry Engineering College, Pillaichavady, Puducherry-605104, India ' Pondicherry Engineering College, Pillaichavady, Puducherry-605104, India

Abstract: Metaheuristics is an interesting research area with significant advances in solving problems with optimisation. Substantial advancements in metaheuristic are being made, and various new algorithms are being developed every day. The analyses in this area will undoubtedly be helpful for future improvements. This paper's main objective is to conduct a literature review of some recent algorithms motivated by nature to compare their features. This paper reviews some recently published nature inspired algorithms such as squirrel search algorithm (SSA), improved squirrel search algorithm (ISSA), grey wolf optimiser (GWO) algorithm, random walk grey wolf optimiser (RW_GWO) algorithm, sailfish optimiser (SAO) algorithm, sandpiper optimisation algorithm (SOA), search and rescue operations (SRO) algorithm, slime mould optimisation (SMO) algorithm, grasshopper optimisation algorithm (GOA) and opposition based learning grasshopper optimisation algorithm (OBLGOA). This paper focuses on a brief introduction of these algorithms and key concepts involved in formulation of swarm intelligence. Finally, this work outlines the directions for conducting effective future research.

Keywords: metaheuristics; optimisation; swarm intelligence; improved metaheuristics.

DOI: 10.1504/IJSI.2021.10037176

International Journal of Swarm Intelligence, 2022 Vol.7 No.2, pp.182 - 205

Received: 31 Mar 2020
Accepted: 27 Nov 2020

Published online: 26 May 2022 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article