Coyote优化算法的广义网络模型

Q4 Agricultural and Biological Sciences

International Journal Bioautomation Pub Date : 2022-12-01 DOI:10.7546/ijba.2022.26.4.000787

O. Roeva, Dafina Zoteva, P. Vassilev

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引用次数: 0

摘要

本文用广义网络(GNs)的方法描述了COA算法的功能。COA是一种基于种群的优化元启发式算法，其灵感来自犬类。在基于种群的元启发式通用gn -模型的基础上，通过设置gn -令牌的不同特征函数，构建了COA的gn -模型。提出的gn模型成功地描述了所考虑的元启发式算法，执行基本步骤并执行最优搜索。

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Generalized Net Model of Coyote Optimization Algorithm

In the presented paper, the functioning of the coyote optimization algorithm (COA) is described using the apparatus of generalized nets (GNs). The COA is a population-based metaheuristic for optimization inspired by the Canis latrans species. Based on a Universal GN-model of population-based metaheuristics, а GN-model of COA is constructed by setting different characteristic functions of the GN-tokens. The presented GN-model successfully describes the considered metaheuristic algorithm, conducting basic steps and performing an optimal search.

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来源期刊

International Journal Bioautomation Agricultural and Biological Sciences-Food Science

CiteScore

1.10

自引率

0.00%

发文量

审稿时长

12 weeks