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A new mycorrhized tree optimization nature-inspired algorithm
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AI
DOI：10.1007/s00500-022-06865-8.png)
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Abstract
En 中文
In this article, we are presenting a new nature-inspired metaheuristic optimization algorithm that we call the Mycorrhiza Tree Optimization Algorithm (MTOA) focused on solving optimization problems. The algorithm is inspired by the relationship between trees and the Mycorrhiza Network (MN). In this relationship, there are interactions such as defense, communication, resource exchange and habitat colonization between the Trees and the MN. The Lotka-Volterra continuous systems (Predator-Prey, Cooperative and Competitive Models) were used for the design of the algorithm. To verify the efficiency of the algorithm, experiments with 36 mathematical functions were performed, but we are only presenting results of the functions with which comparisons were made with other methods. Hypothesis tests were also carried out, where in most of the results the MTOA algorithm was better by 70% and only in the experiments in 100 dimensions it was better by 60%. We believe that the algorithm has the potential to solve problems in control and optimization of neural networks, for which experimentation will be done as future work.
Keywords:
Optimization
Metaheuristic
Trees
Mycorrhiza
Lotka-Volterra
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2.5
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1.0W
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2.1W
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