MOTEO: a novel multi-objective thermal exchange optimization algorithm for engineering problems


  • Nima Khodadadi, Siamak Talatahari, Armin Dadras Eslamlou

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  • 15 April 2022

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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