Generalized Net Model of Coyote Optimization Algorithm

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

Abstract

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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Coyote优化算法的广义网络模型
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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来源期刊
International Journal Bioautomation
International Journal Bioautomation Agricultural and Biological Sciences-Food Science
CiteScore
1.10
自引率
0.00%
发文量
22
审稿时长
12 weeks
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