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The multiple team formation problem using sociometry

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posted on 30.04.2018 by Jimmy H. Gutierrez, Cesar A. Astudillo, Pablo Ballesteros-Perez, Daniel Mora-Melia, Alfredo Candia-Vejar
© 2016 The Authors. Published by Elsevier Ltd. The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes. Specifically, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP). Second, an optimisation model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimisation model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most efficient in almost all cases. Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research.

Funding

This research study was funded in Chile by CONICYT under the Programs Initiation Into Research 2012, 2013 and 2014 (Project numbers 11121350, 11130666 and 11140128). Open Access of this manuscript was funded by the School of Construction Management and Engineering of the University of Reading (United Kingdom).

History

School

  • Architecture, Building and Civil Engineering

Published in

Computers and Operations Research

Volume

75

Pages

150 - 162

Citation

GUTIERREZ, J.H. ...et al., 2016. The multiple team formation problem using sociometry. Computers and Operations Research, 75, pp. 150-162.

Publisher

© The Authors. Published by Elsevier

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

19/05/2016

Publication date

2016-05-22

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

0305-0548

Language

en

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