Título The Machine-Part Cell Formation Problem with Non-Binary Values: A MILP Model and a Case of Study in the Accounting Profession
Autores Joaquin del Pozo-Antunez, Jose , FERNÁNDEZ NAVARRO, FRANCISCO DE ASÍS, MOLINA SÁNCHEZ, HORACIO, ARIZA MONTES, JOSÉ ANTONIO, CARBONERO RUZ, MARIANO
Publicación externa No
Medio Mathematics
Alcance Article
Naturaleza Científica
Cuartil JCR 1
Cuartil SJR 3
Ámbito Internacional
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111727500&doi=10.3390%2fmath9151768&partnerID=40&md5=69ac939162470605e2565e188975fcc9
Fecha de publicacion 01/08/2021
ISI 000682043900001
Scopus Id 2-s2.0-85111727500
DOI 10.3390/math9151768
Abstract The traditional machine-part cell formation problem simultaneously clusters machines and parts in different production cells from a zero-one incidence matrix that describes the existing interactions between the elements. This manuscript explores a novel alternative for the well-known machine-part cell formation problem in which the incidence matrix is composed of non-binary values. The model is presented as multiple-ratio fractional programming with binary variables in quadratic terms. A simple reformulation is also implemented in the manuscript to express the model as a mixed-integer linear programming optimization problem. The performance of the proposed model is shown through two types of empirical experiments. In the first group of experiments, the model is tested with a set of randomized matrices, and its performance is compared to the one obtained with a standard greedy algorithm. These experiments showed that the proposed model achieves higher fitness values in all matrices considered than the greedy algorithm. In the second type of experiment, the optimization model is evaluated with a real-world problem belonging to Human Resource Management. The results obtained were in line with previous findings described in the literature about the case study.
Palabras clave machine-part cell formation problem; fractional 0-1 programming; mixed-integer linear programming; human resources management
Miembros de la Universidad Loyola

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