Three Genetic Algorithm Approaches to the Unrelated Parallel Machine Scheduling Problem with Limited Human Resources

Fulvio Antonio Cappadonna, Antonio Costa, Sergio Fichera

Abstract

This paper addresses the unrelated parallel machine scheduling problem with limited and differently-skilled human resources. Firstly, the formulation of a Mixed Integer Linear Programming (MILP) model for solving the problem is provided. Then, three proper Genetic Algorithms (GAs) are presented, aiming to cope with larger sized issues. Numerical experiments put in evidence how all GAs proposed are able to approach the global optimum given by MILP model for small-sized instances. Moreover, a statistical comparison among proposed meta-heuristics algorithms is performed with reference to larger problems.

References

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Paper Citation


in Bibtex Style

@conference{ecta12,
author={Fulvio Antonio Cappadonna and Antonio Costa and Sergio Fichera},
title={Three Genetic Algorithm Approaches to the Unrelated Parallel Machine Scheduling Problem with Limited Human Resources},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={170-175},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004116501700175},
isbn={978-989-8565-33-4},
}


in Harvard Style

Cappadonna F., Costa A. and Fichera S. (2012). Three Genetic Algorithm Approaches to the Unrelated Parallel Machine Scheduling Problem with Limited Human Resources . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 170-175. DOI: 10.5220/0004116501700175


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - Three Genetic Algorithm Approaches to the Unrelated Parallel Machine Scheduling Problem with Limited Human Resources
SN - 978-989-8565-33-4
AU - Cappadonna F.
AU - Costa A.
AU - Fichera S.
PY - 2012
SP - 170
EP - 175
DO - 10.5220/0004116501700175