RCMeans: A Recursive Capacitated Means for Districting Problem

  • Polyana Bezerra Costa Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Italo Francyles Santos da Silva Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Pedro Henrique Carvalho Vieira Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Robert Douglas Araújo Santos Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Mayara Gomes Silva Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Christyellen Souza Costa Lima Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Daniel Lima Gomes Júnior Federal University of Maranhão, Applied Computing Center, São Luís-MA, Brazil
  • Eliana Márcia Garros Equatorial Energia, Companhia Energética do Maranhão, São Luís-MA, Brazil
  • Italo Fernandes Serra da Silva Equatorial Energia, Companhia Energética do Maranhão, São Luís-MA, Brazil
  • Lucas Paula Assunção Pinheiro Equatorial Energia, Companhia Energética do Maranhão, São Luís-MA, Brazil

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.

Published
2018-10-18
How to Cite
COSTA, Polyana Bezerra et al. RCMeans: A Recursive Capacitated Means for Districting Problem. Journal on Advances in Theoretical and Applied Informatics, [S.l.], v. 4, n. 1, p. 28-35, oct. 2018. ISSN 2447-5033. Available at: <http://revista.univem.edu.br/jadi/article/view/2745>. Date accessed: 13 nov. 2018. doi: https://doi.org/10.26729/jadi.v4i1.2745.