Performance Analysis of Vegetation Evolution
Performance Analysis of Vegetation Evolution
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DOI：
10.1109/smc.2019.8913887
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Jun Yu;H. Takagi
中科院分区：
文献类型：
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作者：
Jun Yu;H. Takagi
我们专注于分析建议植被进化（VEGE）算法的操作对其性能的影响，而不是将其与其他EC算法进行比较，即，研究VEGE算法的每个组件对其性能的影响。为了进一步分析VEGE算法的性能，我们设计了一系列的控制实验，通过在3个不同维度的28个基准函数上运行它们来调查每个VEGE组件的贡献。随后，我们总结了一些经验，设置VEGE参数，应用VEGE优化任务。实验结果表明，成熟度操作对算法性能有重要影响，个体的生长操作次数越少越好，而生成种子个体的数量不是影响算法性能的重要因素。此外，我们发现人口规模应逐渐增加的维数增加。最后，我们指出了几个潜在的研究方向。
We focus on analyzing the impact of operations of a proposed Vegetation evolution (VEGE) algorithm on its performance rather than compare it with other EC algorithms, i.e., investigate the impact of each component of the VEGE algorithm on its performance. To further analyze the performance of VEGE algorithm, we design a series of controlled experiments to investigate the contribution of each VEGE component by running them on 28 benchmark functions of 3 different dimensions. Subsequently, we summarize some our experiences on setting VEGE parameters to apply the VEGE to optimization tasks. The experimental results reveal that the maturity operation has a critical impact on performance and the number of growth operations of an individual is set as small as possible, while the number of generated seed individuals is not an important factor. Besides, we discover that population size should be gradually increased as the dimension increases. Finally, we point out several potential research directions.