MOTEO: multi-objective thermal exchange optimization

The algorithm is developed based on the concept of Newtonian cooling law.
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Updated 17 Apr 2022

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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.
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% MOTEO: a novel multi-objective thermal exchange %
% optimization algorithm for engineering problems %
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% Developed in MATLAB R2020b (MacOs-Monterey) %
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% Author and programmer %
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% Nima Khodadadi Armin Dadras Eslamlou %
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% inimakhan@me.com %
% nkhod002@fiu.edu % %
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% https://nimakhodadadi.com %
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% 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 %
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Cite As

Nima Khodadadi (2024). MOTEO: multi-objective thermal exchange optimization (https://www.mathworks.com/matlabcentral/fileexchange/110270-moteo-multi-objective-thermal-exchange-optimization), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2022a
Compatible with any release
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Version Published Release Notes
1.0.0