Multi-Objective Jellyfish Search (MOJS) Algorithm

Versión 1.0.0 (6,91 KB) por nhat truong
This study develops a Multi-Objective Jellyfish Search (MOJS) algorithm to solve engineering problems optimally with multiple objectives.
0.0
(0)
520 Descargas
Actualizado 18 sep 2020

Ver licencia

This study develops a Multi-Objective Jellyfish Search (MOJS) algorithm to solve engineering problems optimally with multiple objectives. Lévy flight, elite population, fixed-size archive, chaotic map, and the opposition-based jumping method are integrated into the MOJS to obtain the Pareto optimal solutions. These techniques are employed to define the motions of jellyfish in an ocean current or a swarm in multi-objective search spaces.

Citar como

Chou, Jui-Sheng, and Dinh-Nhat Truong. “Multiobjective Optimization Inspired by Behavior of Jellyfish for Solving Structural Design Problems.” Chaos, Solitons & Fractals, vol. 135, Elsevier BV, June 2020, p. 109738, doi:10.1016/j.chaos.2020.109738.

Ver más estilos
Compatibilidad con la versión de MATLAB
Se creó con R2016a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Etiquetas Añadir etiquetas
Abrir en una nueva pestaña
Versión Publicado Notas de la versión
1.0.0