Capacitated clustering problems applied to the layout of IT-teams in software factories

Marcos J. Negreiros (), Nelson Maculan (), Pablor L. Batista (), João A. Rodrigues () and Augusto W. C. Palhano ()
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Marcos J. Negreiros: Universidade Estadual do Ceará, Mestrado Profissional em Computação Aplicada (MPCUMP-UECE-IFCE) Laboratório de Computação Científica (LCC)
Nelson Maculan: Universidade Federal do Rio de Janeiro Programa de Eng de Sistemas e Computação (PESC-COPPE)
Pablor L. Batista: Universidade Estadual do Ceará, Mestrado Profissional em Computação Aplicada (MPCUMP-UECE-IFCE) Laboratório de Computação Científica (LCC)
João A. Rodrigues: Universidade Estadual do Ceará, Mestrado Profissional em Computação Aplicada (MPCUMP-UECE-IFCE) Laboratório de Computação Científica (LCC)
Augusto W. C. Palhano: Universidade Estadual do Ceará, Mestrado Profissional em Computação Aplicada (MPCUMP-UECE-IFCE) Laboratório de Computação Científica (LCC)

Annals of Operations Research, 2022, vol. 316, issue 2, No 19, 1157-1185

Abstract: Abstract This work studies Heterogeneous Capacitated Clustering Problems (HCCP) which are variations of the Capacitated Clustering Problem (CCP). They are applied to the layout of IT-Teams in software factory. In the real problem, there are workstations placed along the software factory where they are disposed in a pattern the individuals working in the same project form a group that would be geographically close to each other. The groups are heterogeneous in the number of individuals. The general problem discussed here consider a given number of individuals with attributes (weight and coordinates in Euclidean space), and wishes to determine minimum dissimilar clusters constrained to a given maximum capacity for each cluster. The groups are formed to achieve a specific objective of just forming feasible capacitated compact groups and/or also including the position of the group manager. The models here presented and evaluated consider a new generalized version of the heterogeneous capacitated median problem (gHCMP) which extracts the medians from the set of individuals; a new formulation is introduced for the min-max diameter heterogeneous capacitated clustering problem; a new formulation for the minimum group distance heterogeneous capacitated clustering problem; and a new formulation using the HCCCP. We also discuss ways to obtain the best results from the proposed formulations using adequate solvers for each problem; and it is presented a metaheuristic framework for the HCCCP that solves close to optimality all the real instances here tested. We also present the results obtained from the formulations and metaheuristic related to instances that represent real situations about organizing the layout of two Brazilian software factories. The proposed gHCMP model outperform the solutions obtained for the evaluated instances also using the other models.

Keywords: Capacitated clustering problem; Mathematical programming modeling; Solvers (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-020-03785-4

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