Algorithm based on GRASP metaheuristics to solve the problem of the maximum diversity applied in the confirmation of work teams

Authors

DOI:

https://doi.org/10.13140/RG.2.2.20161.51046

Keywords:

Metaheuristic, GRASP, maximun diversity problem, work teams

Abstract

This paper addresses the problem of forming work teams in the most diverse way possible, given that it is demonstrated that work teams that are diverse, functionally and demographically, are more efficient in solving problems. For this purpose, we adapted an optimization model to a maximum diversity problem, with the creation of an algorithm based on GRASP metaheuristics this was efficient. In the investigation, a solution algorithm is proposed for this case of combinatorial optimization problem, it is type of strongly np-hard, the algorithm was used specifically for the conformation of survey teams, they collect data for different surveys prepared by the National Institute of Statistics and Census of Ecuador.

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Author Biographies

Livino Manuel Armijos Toro, Universidad de las Fuerzas Armadas, Ecuador

Ingeniero en Estadística Informática, Magíster en Control de Operaciones y Gestión Logística y Magíster en Administración de Empresas mención Finanzas. Profesor Auxiliar e Investigador de la Universidad de las Fuerzas Armadas, Ecuador. Correo: lmarmijos2@espe.edu.ec

Fernando Francisco Sandoya Sánchez, Escuela Superior Politécnica del Litoral. Ecuador

Matemático, Magíster en Investigación de Operaciones, Magíster en Gestión Logística y Doctor en Ingeniería en Sistemas–Investigación de Operaciones. Profesor titular e investigador en la Escuela Superior Politécnica del Litoral. Ecuador. Correo: fsandoya@espol.edu.ec

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Publicaciones en Ciencias y Tecnología Vol 13 nro 1 Año 2019

Published

2019-06-30

How to Cite

[1]
L. M. Armijos Toro and F. F. Sandoya Sánchez, “Algorithm based on GRASP metaheuristics to solve the problem of the maximum diversity applied in the confirmation of work teams”, Publ.Cienc.Tecnol, vol. 13, no. 1, pp. 15-29, Jun. 2019.

Issue

Vol. 13 No. 1 (2019): January-June

Section

Research Article

Copyright (c) 2019 Livino Manuel Armijos Toro, Fernando Francisco Sandoya Sánchez

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