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首页> 外文期刊>Scientific Research and Essays >A novel meta-heuristic algorithm for numerical function optimization: Blind, naked mole-rats (BNMR) algorithm
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A novel meta-heuristic algorithm for numerical function optimization: Blind, naked mole-rats (BNMR) algorithm

机译:一种用于数值函数优化的新型元启发式算法:盲人裸鼠(BNMR)算法

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Optimization algorithms inspired by the world of nature have turned into powerful tools for solving the complicated problems. However, they have still some drawbacks need the investigation of new and better optimization algorithms. In this paper, we propose a new meta-heuristic algorithm called blind naked mole-rats (BNMR) algorithm. This algorithm has been developed based on the social behavior of the blind naked mole-rats colony in searching the food and protecting the colony against invasions. By introducing this algorithm, we have tried to overcome many disadvantages of the usual optimization algorithms including getting trapped in local minimums or having low rate of convergence. Using several benchmark functions, we demonstrate the superior performance of the proposed algorithm in comparison with some other well-known optimization algorithms.
机译:受自然界启发的优化算法已成为解决复杂问题的强大工具。但是,它们仍然存在一些缺点,需要研究新的更好的优化算法。在本文中,我们提出了一种新的元启发式算法,称为盲裸mole鼠(BNMR)算法。该算法是基于盲人裸mole鼠种群在寻找食物和保护菌落免受入侵方面的社会行为而开发的。通过引入此算法,我们尝试克服了常规优化算法的许多缺点,包括陷入局部最小值或收敛速度低。通过使用几个基准函数,我们证明了与其他一些著名的优化算法相比,该算法的优越性能。

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