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Authors: Francesco Longo ; Andrea Rocco Lotronto ; Marco Scarpa and Antonio Puliafito

Affiliation: Università degli Studi di Messina, Italy

Keyword(s): Routine Maintenance Interventions, Metaheuristic Approaches, Simulated Annealing, Scheduling Problems, Optimization Problems.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Operational Research ; Problem Solving ; Scheduling and Planning ; Strategic Decision Support Systems

Abstract: Simulated annealing is a metaheuristic approach for the solution of optimization problems inspired to the controlled cooling of a material from a high temperature to a state in which internal defects of the crystals are minimized. In this paper, we apply a simulated annealing approach to the scheduling of geographically distributed routine maintenance interventions. Each intervention has to be assigned to a maintenance team and the choice among the available teams and the order in which interventions are performed by each team are based on team skills, cost of overtime work, and cost of transportation. We compare our solution algorithm versus an exhaustive approach considering a real industrial use case and show several numerical results to analyze the effect of the parameters of the simulated annealing on the accuracy of the solution and on the execution time of the algorithm.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Longo, F.; Rocco Lotronto, A.; Scarpa, M. and Puliafito, A. (2015). Optimizing Routine Maintenance Team Routes. In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-096-3; ISSN 2184-4992, SciTePress, pages 535-546. DOI: 10.5220/0005400105350546

@conference{iceis15,
author={Francesco Longo. and Andrea {Rocco Lotronto}. and Marco Scarpa. and Antonio Puliafito.},
title={Optimizing Routine Maintenance Team Routes},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2015},
pages={535-546},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005400105350546},
isbn={978-989-758-096-3},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Optimizing Routine Maintenance Team Routes
SN - 978-989-758-096-3
IS - 2184-4992
AU - Longo, F.
AU - Rocco Lotronto, A.
AU - Scarpa, M.
AU - Puliafito, A.
PY - 2015
SP - 535
EP - 546
DO - 10.5220/0005400105350546
PB - SciTePress