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Authors: Daniel J. Caetano and Nicolau D. F. Gualda

Affiliation: Universidade de São Paulo and Escola Politécnica, Brazil

ISBN: 978-989-8425-83-6

Keyword(s): Air transportation, Schedule generation, Fleet assignment, Metaheuristic, Ant system.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Hybrid Systems ; Soft Computing ; Swarm/Collective Intelligence

Abstract: Schedule Generation and Fleet Assignment problems usually are solved separately. The integrated solution for both problems, although desirable, leads to large scale models of the NP-Hard class. This article presents a mathematical formulation of this integrated problem along with a new heuristical approach, called MAGS, based on the ACO metaheuristic. Both the exact solution and the one provided by MAGS are obtained and compared for the case of a Brazilian airline. The results have shown the applicability of MAGS to real world cases.

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Paper citation in several formats:
J. Caetano, D. and D. F. Gualda, N. (2011). MAGS - An Aco-based Model to Solve the Schedule Generation and Fleet Assignment Integrated Problem.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 227-232. DOI: 10.5220/0003673502270232

@conference{ecta11,
author={Daniel J. Caetano. and Nicolau D. F. Gualda.},
title={MAGS - An Aco-based Model to Solve the Schedule Generation and Fleet Assignment Integrated Problem},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)},
year={2011},
pages={227-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003673502270232},
isbn={978-989-8425-83-6},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)
TI - MAGS - An Aco-based Model to Solve the Schedule Generation and Fleet Assignment Integrated Problem
SN - 978-989-8425-83-6
AU - J. Caetano, D.
AU - D. F. Gualda, N.
PY - 2011
SP - 227
EP - 232
DO - 10.5220/0003673502270232

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