Monarch butterfly optimization: a comprehensive review

Y Feng, S Deb, GG Wang, AH Alavi - Expert Systems with Applications, 2021 - Elsevier
Swarm intelligence (SI) is the collective behavior of decentralized, self-organized natural or
artificial systems. Monarch butterfly optimization (MBO) algorithm is a class of swarm …

Elephant herding optimization: variants, hybrids, and applications

J Li, H Lei, AH Alavi, GG Wang - Mathematics, 2020 - mdpi.com
Elephant herding optimization (EHO) is a nature-inspired metaheuristic optimization
algorithm based on the herding behavior of elephants. EHO uses a clan operator to update …

A survey of learning-based intelligent optimization algorithms

W Li, GG Wang, AH Gandomi - Archives of Computational Methods in …, 2021 - Springer
A large number of intelligent algorithms based on social intelligent behavior have been
extensively researched in the past few decades, through the study of natural creatures, and …

Binary butterfly optimization approaches for feature selection

S Arora, P Anand - Expert Systems with Applications, 2019 - Elsevier
In this paper, binary variants of the Butterfly Optimization Algorithm (BOA) are proposed and
used to select the optimal feature subset for classification purposes in a wrapper-mode. BOA …

Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issues

R Priyadarshi, B Gupta, A Anurag - The Journal of Supercomputing, 2020 - Springer
Wireless sensor networks (WSNs) have been considered as one of the fine research areas
in recent years because of vital role in numerous applications. To process the extracted data …

Behavior of crossover operators in NSGA-III for large-scale optimization problems

JH Yi, LN Xing, GG Wang, J Dong, AV Vasilakos… - Information …, 2020 - Elsevier
Traditional multi-objective optimization evolutionary algorithms (MOEAs) do not usually meet
the requirements for online data processing because of their high computational costs. This …

Improving NSGA-III algorithms with information feedback models for large-scale many-objective optimization

ZM Gu, GG Wang - Future Generation Computer Systems, 2020 - Elsevier
Recently, more and more multi/many-objective algorithms have been proposed. However,
most evolutionary algorithms only focus on solving small-scale multi/many-objective …

Predicting protein structural classes for low-similarity sequences by evaluating different features

XJ Zhu, CQ Feng, HY Lai, W Chen, L Hao - Knowledge-Based Systems, 2019 - Elsevier
Protein structural class could provide important clues for understanding protein fold,
evolution and function. However, it is still a challenging problem to accurately predict protein …

Review of economic dispatch in multi-area power system: State-of-the-art and future prospective

AB Kunya, AS Abubakar, SS Yusuf - Electric Power Systems Research, 2023 - Elsevier
Efficient and cost-effective coordination of online generation facilities is essential to the
reliable operation multi-area power system (PS) especially in a deregulated environment …

Recent methodology-based gradient-based optimizer for economic load dispatch problem

S Deb, DS Abdelminaam, M Said, EH Houssein - IEEE Access, 2021 - ieeexplore.ieee.org
Economic load dispatch (ELD) in power system problems involves scheduling the power
generating units to minimize cost and satisfy system constraints. Although previous works …