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An Improved Biology Migration Algorithm with Von Neumann Structure

机译:冯·诺依曼结构的一种改进的生物迁移算法

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Biology migration algorithm (BMA) is a newly developed metaheuristic algorithm inspired by the biology migration phenomenon. The paramount challenge in BMA is that it is prone to stagnation in local optima and premature convergence. To solve these issues, this paper proposed an improved biology migration algorithm with Von Neumann structure to help BMA balance exploration and exploitation better, which named BMAVI. First, non-linear initial weights are introduced into BMA to balance exploration and exploitation. Second, the Von Neumann structure was introduced into the BMA to construct the neighbors of each individual, increasing information exchange and enriching population diversity. Finally, the proposed BMAVI has also been evaluated on CEC2017 test set compared with the classic and other novel evolutionary algorithms to confirm the performance of BMAVI. Experimental results show that the performance of the proposed BMAVI algorithm is better than other selected algorithms.
机译:生物迁移算法(BMA)是受生物学迁移现象启发而开发的一种新的启发式算法。 BMA中最重要的挑战是,它在局部最优和过早收敛中容易停滞。为解决这些问题,本文提出了一种改进的具有冯·诺依曼结构的生物迁移算法,以帮助BMA更好地平衡勘探与开发,并将其命名为BMAVI。首先,将非线性初始权重引入BMA,以平衡勘探和开发。其次,冯·诺伊曼(Von Neumann)结构被引入BMA,以构建每个人的邻居,从而增加信息交流并丰富人口多样性。最后,还将拟议的BMAVI在CEC2017测试集上与经典算法和其他新颖的进化算法进行了比较,以确认BMAVI的性能。实验结果表明,所提出的BMAVI算法的性能优于其他算法。

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