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Effective adaptive large neighborhood search for a firefighters timetabling problem

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Abstract

Every year, wildfires accentuated by global warming, cause economic and ecological losses, and often, human casualties. Increasing operational capacity of firefighter crews is of utmost importance to better face the forest fire period that yearly occurs. In this study, we investigate the real-world firefighters timetabling problem of the INFOCA institution, Andalusia (Spain). The main issue is to achieve maximum operational capability while taking into account work regulation constraints. This paper proposes an Integer Linear Programming (ILP) formulation that makes it feasible to solve small/medium instances to optimality. We put forward a matheuristic (ILPH) based on the ILP formulation, and we obtain solutions for larger instances. We propose an Adaptive Large Neighbourhood Search metaheuristic (ALNS) to obtain better results for larger instances and we use a version of the ILPH as one of the constructive methods. The ALNS obtains all the optimal solutions found by the ILP on small instances. It yields better solutions than the ILPH matheuristic on larger instances within shorter processing times. We report on experiments performed on datasets generated using real-world data of the INFOCA institution. The work was initiated as part of the GEO-SAFE project.

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  1. https://datasets.hds.utc.fr/project/10

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Acknowledgements

This work was initiated as part of the GEO-SAFE project. The GEO-SAFE project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłłodowska-Curie RISE grant agreement No 691161. This work is carried out in the framework of the Labex MS2T, which was funded by the French Government, through the program “Investments for the future“ managed by the National Agency for Research (Reference ANR-11-IDEX-0004-02).

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  1. CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), Université de Technologie de Compiègne, CS 60 319, 60 203, Compiègne Cedex, France

    Mohamed-Amine Ouberkouk, Jean-Paul Boufflet & Aziz Moukrim

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  1. Mohamed-Amine Ouberkouk
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  2. Jean-Paul Boufflet
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Correspondence to Mohamed-Amine Ouberkouk.

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Ouberkouk, MA., Boufflet, JP. & Moukrim, A. Effective adaptive large neighborhood search for a firefighters timetabling problem. J Heuristics 29, 545–580 (2023). https://doi.org/10.1007/s10732-023-09519-6

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  • DOI: https://doi.org/10.1007/s10732-023-09519-6

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