@article{JADI, author = {Polyana Costa and Italo Santos da Silva and Pedro Carvalho Vieira and Robert Araújo Santos and Mayara Silva and Christyellen Costa Lima and Daniel Gomes Júnior and Eliana Garros and Italo Serra da Silva and Lucas Assunção Pinheiro}, title = { RCMeans: A Recursive Capacitated Means for Districting Problem}, journal = {Journal on Advances in Theoretical and Applied Informatics}, volume = {4}, number = {1}, year = {2018}, keywords = {}, abstract = {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.}, issn = {2447-5033}, pages = {28--35}, doi = {10.26729/jadi.v4i1.2745}, url = {https://revista.univem.edu.br/jadi/article/view/2745} }