MOTEO: multi-objective thermal exchange optimization

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

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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

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.

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MATLAB Release Compatibility
Created with R2022a
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Version Published Release Notes
1.0.1

The citation was added.

1.0.0