MOTEO: multi-objective thermal exchange optimization

The algorithm is developed based on the concept of Newtonian cooling law.
318 Downloads
Updated 13 Jun 2024

View License

In the present paper, a physics-inspired metaheuristic algorithm is presented to solve multi-objective optimization problems. The algorithm is developed based on the concept of Newtonian cooling law that recently has been employed by the thermal exchange optimization (TEO) algorithm to solve single-objective optimization problems efficiently. The performance of the multi-objective version of TEO (MOTEO) is examined through bi- and tri-objective mathematical and engineering problems as well as bi-objective structural design examples. According to the comparisons between the MOTEO and several well-known algorithms, the proposed algorithm can provide quality Pareto fronts with appropriate accuracy, uniformity, and coverage for multi-objective problems.
%__________________________________________________________________ %
% %
% %
% MOTEO: a novel multi-objective thermal exchange %
% optimization algorithm for engineering problems %
% %
% %
% Developed in MATLAB R2020b (MacOs-Monterey) %
% %
% Author and programmer %
% --------------------------------- %
% Nima Khodadadi Armin Dadras Eslamlou %
% %
% %
% %
% %
% e-Mail(2) %
% --------------------------------- %
% inimakhan@me.com %
% nkhod002@fiu.edu % %
% %
% %
% https://nimakhodadadi.com %
% %
% %
% %
% %
% Cite this article %
% Khodadadi, N., Talatahari, S. & Dadras Eslamlou, %
% MOTEO: a novel multi-objective thermal exchange optimization %
% algorithm for engineering problems. Soft Comput (2022). %
% https://doi.org/10.1007/s00500-022-07050-7 %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Cite As

Khodadadi, Nima, et al. “MOTEO: a Novel Multi-Objective Thermal Exchange Optimization Algorithm for Engineering Problems.” Soft Computing, vol. 26, no. 14, Springer Science and Business Media LLC, Apr. 2022, pp. 6659–84, doi:10.1007/s00500-022-07050-7.

View more styles
MATLAB Release Compatibility
Created with R2022a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.1

The citation was added.

1.0.0