Multi-Objective Jellyfish Search (MOJS) Algorithm

Version 1.0.0 (6.91 KB) by nhat truong
This study develops a Multi-Objective Jellyfish Search (MOJS) algorithm to solve engineering problems optimally with multiple objectives.
0.0
(0)
518 Downloads
Updated 18 Sep 2020

View License

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.

Cite As

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.

View more styles
MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Version Published Release Notes
1.0.0