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Heat transfer relation-based optimization algorithm (HTOA)

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Abstract

Novel metaheuristic algorithms are now considered an appealing collection of methods for solving complex optimization problems, in which the challenging objective is to find a better solution in a shorter computation time. Focusing on the same objective, this paper proposes a novel metaheuristic optimization algorithm inspired by heat transfer relationships based on the second law of thermodynamics. Imitating the heat transfer behavior of solid objects, the proposed method is called the heat transfer relation-based optimization algorithm (HTOA). This behavior was modeled on a heat transfer function used to measure temperature differences between the selected solutions and the best solution. This function was employed to determine and add the heat capacity transferred between those solutions. Finally, all the solutions were heat-exchanged with the best solution to select the fittest solution and exclude the rest. This procedure continued until the best solution or solutions were found. The proposed method is challenged by many famous benchmark problems in two categories as well as two real-world problems (PID controller and linear regression). The HTOA was then compared with a number of well-known and state-of-the-art optimization algorithms. Selecting better solutions and requiring shorter computation time, the proposed HTOA outperformed the other algorithms.

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Authors and Affiliations

  1. Department of Computer Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran

    Foad Asef & Vahid Majidnezhad

  2. Department of Computer Engineering, University of Tabriz, Tabriz, Iran

    Mohammad-Reza Feizi-Derakhshi

  3. Department of Computer Engineering, Iran Science and Technology University, Tehran, Iran

    Saeed Parsa

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  1. Foad Asef
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Asef, F., Majidnezhad, V., Feizi-Derakhshi, MR. et al. Heat transfer relation-based optimization algorithm (HTOA). Soft Comput 25, 8129–8158 (2021). https://doi.org/10.1007/s00500-021-05734-0

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