An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges

K Rajwar, K Deep, S Das - Artificial Intelligence Review, 2023 - Springer
As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

Metaheuristics: a comprehensive overview and classification along with bibliometric analysis

AE Ezugwu, AK Shukla, R Nath, AA Akinyelu… - Artificial Intelligence …, 2021 - Springer
Research in metaheuristics for global optimization problems are currently experiencing an
overload of wide range of available metaheuristic-based solution approaches. Since the …

Snake Optimizer: A novel meta-heuristic optimization algorithm

FA Hashim, AG Hussien - Knowledge-Based Systems, 2022 - Elsevier
In recent years, several metaheuristic algorithms have been introduced in engineering and
scientific fields to address real-life optimization problems. In this study, a novel nature …

Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications

W Zhao, Z Zhang, L Wang - Engineering Applications of Artificial …, 2020 - Elsevier
A new bio-inspired optimization technique, named Manta Ray Foraging Optimization
(MRFO) algorithm, is proposed and presented, aiming to providing a novel algorithm that …

Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations

D Molina, J Poyatos, JD Ser, S García, A Hussain… - Cognitive …, 2020 - Springer
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

Recent advances in harris hawks optimization: A comparative study and applications

AG Hussien, L Abualigah, R Abu Zitar, FA Hashim… - Electronics, 2022 - mdpi.com
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …

A novel atom search optimization for dispersion coefficient estimation in groundwater

W Zhao, L Wang, Z Zhang - Future Generation Computer Systems, 2019 - Elsevier
A new type of meta-heuristic global optimization methodology based on atom dynamics is
introduced. The proposed Atom Search Optimization (ASO) approach is a population-based …

Supply-demand-based optimization: A novel economics-inspired algorithm for global optimization

W Zhao, L Wang, Z Zhang - Ieee Access, 2019 - ieeexplore.ieee.org
A novel metaheuristic optimization algorithm, named supply-demand-based optimization
(SDO), is presented in this paper. SDO is a swarm-based optimizer motivated by the supply …

Socio evolution & learning optimization algorithm: A socio-inspired optimization methodology

M Kumar, AJ Kulkarni, SC Satapathy - Future Generation Computer …, 2018 - Elsevier
The paper proposes a novel metaheuristic Socio Evolution & Learning Optimization
Algorithm (SELO) inspired by the social learning behaviour of humans organized as families …

EJS: Multi-strategy enhanced jellyfish search algorithm for engineering applications

G Hu, J Wang, M Li, AG Hussien, M Abbas - Mathematics, 2023 - mdpi.com
The jellyfish search (JS) algorithm impersonates the foraging behavior of jellyfish in the
ocean. It is a newly developed metaheuristic algorithm that solves complex and real-world …