The improved mayfly optimization algorithm

37Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The mayfly optimization (MO) algorithm was proposed with a better hybridization of the particle swarm optimization (PSO) and the differential evolution (DE) algorithms. The velocity would be relevant to the Cartesian distance among the relevant individuals. In this paper, a reasonable revision for the velocity updating equations was proposed based on the idea of moving towards each other as capable as they can. Simulation results proved that the improved MO algorithm would perform better than the original one.

References Powered by Scopus

Grey Wolf Optimizer

15586Citations
N/AReaders
Get full text

Equilibrium optimizer: A novel optimization algorithm

1850Citations
N/AReaders
Get full text

A literature survey of benchmark functions for global optimisation problems

1119Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Deep learning-based skin lesion diagnosis model using dermoscopic images

76Citations
N/AReaders
Get full text

Optimal design of Photovoltaic, Biomass, Fuel Cell, Hydrogen Tank units and Electrolyzer hybrid system for a remote area in Egypt

45Citations
N/AReaders
Get full text

Application of novel binary optimized machine learning models for monthly streamflow prediction

35Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Gao, Z. M., Zhao, J., Li, S. R., & Hu, Y. R. (2020). The improved mayfly optimization algorithm. In Journal of Physics: Conference Series (Vol. 1684). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1684/1/012077

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

67%

Professor / Associate Prof. 1

17%

Lecturer / Post doc 1

17%

Readers' Discipline

Tooltip

Physics and Astronomy 1

33%

Computer Science 1

33%

Engineering 1

33%

Save time finding and organizing research with Mendeley

Sign up for free