驴定理优化

M. Dehghani, M. Mardaneh, O. Malik, S. M. NouraeiPour
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引用次数: 25

摘要

近年来,元启发式优化算法在许多应用中得到了应用。这些算法大多受到物理过程或生物行为的启发。本文提出了一种新的优化算法,称为驴定理优化算法(DTO),它模拟了驴的行为。DTO是基于驴定理,模仿驴的行为,以获取食物。该算法在23个知名基准测试函数上进行了测试,并与8种优化算法进行了性能比较。结果表明,与其他已知的优化算法相比,DTO能够提供更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DTO: Donkey Theorem Optimization
Metaheuristic optimization algorithms have been used in many applications in recent years. Most of these algorithms are inspired by physical processes or living beings' behaviors. A new optimization algorithm, called Donkey Theorem Optimization (DTO), that simulates the behavior of Donkeys is proposed in this paper. DTO is based on donkey theorem that mimics behavior of donkey for reach to food. Proposed algorithm is tested on 23 well-known benchmark test functions and its performance compared with eight optimization algorithms. The results show that DTO is able to provide better results as compared to the other well-known optimization algorithms.
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