Abstract
This study presents a new metaheuristic optimization algorithm named Tree Optimization Algorithm (TOA) for solving mathematical benchmark functions and engineering problems. This algorithm, which is inspired from the growth of trees, starts from a random initial population and improves their performance according to the growth pattern of trees. Indeed, the purpose of this new optimization method is to find the highest leaf of a tree by utilizing the position of the best leaf, and also replacing yellow dried leaves by new random fresh green ones. These strategies prevent the algorithm from the premature convergence and getting stuck in local minima. This modern optimization method is evaluated by solving several mathematical test functions and a real world constrained design problem. The obtained results are compared with those of some prominent evolutionary algorithms introduced in the literature. The numerical and simulation results verify the superiority of the TOA in terms of the solution accuracy and the convergence speed.
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Mahmoodabadi, M.J., Rasekh, M. & Yahyapour, M. Tree optimization algorithm (TOA): a novel metaheuristic approach for solving mathematical test functions and engineering problems. Evol. Intel. 16, 1325–1338 (2023). https://doi.org/10.1007/s12065-022-00742-x
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DOI: https://doi.org/10.1007/s12065-022-00742-x