RCMeans:一种求解分区问题的递归赋权方法

P. B. Costa, Italo Francyles Santos da Silva, P. C. S. Vieira, Robert Douglas Araújo Santos, M. G. Silva, Christyellen Souza Costa Lima, Daniel Lima Gomes Junior, Eliana Márcia Garros, I. F. S. Silva, Lucas P. A. Pinheiro
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引用次数: 0

摘要

巴西一家能源分销商的计费流程与阅读能耗物流相关联。高效、平衡且支持容量的流程有利于降低成本并提高所提供服务的质量。在容量聚类中,元素与构建容量有限的组的权重相关联。本文提出了一种研究容量聚类问题的方法,并应用于巴西能源分销公司的消费者单位计量组组织。一般来说,创建这些度量组的过程是由专家分析人员手动执行的。这种问题模式的目的是创建分区,使相关组的内部分散最小化。在这项工作中,提出了基于K-Means技术的RCMeans方法,该方法应用于包含分组定义容量约束的数据分组。在聚聚分析、分组分离、分组数量、剪影指数、分组消费单位测量平均时间等方面,对目前的现状与本文方法的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RCMeans: A Recursive Capacitated Means for Districting Problem
The billing process of an energy distributor in Brazil is connected to reading energy consumption logistics. An efficient, balanced and capacity enabled process has benefits with cost reducing and quality perception of the service provided. In capacitated clustering, the elements are associated with weights for construction of groups with limited capacities. This paper presents an approach to the capacitated clustering problem, applied to the consumer unit measurement groups organization in Brazil's energy distributors companies. The process of creating those measurement groups, in general, is carried out manually by expert analysts. The purpose of this problem modality is to create partitions that minimize the internal dispersion of the associated group. In this work, the RCMeans method, which is based on the K-Means technique applied to data groupings with the inclusion of the capacity constraint for the group definition, is presented. The obtained results show a comparison between the current situation and the result with the proposed method, under the cohesion analysis, separation, number of groups, silhouette index, and consumer units measurement mean time of the groups.
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