Heuristics and meta-heuristic to solve the ROADEF/EURO challenge 2020 maintenance planning problem

Hanyu Gu (), Hue Chi Lam (), Thi Thanh Thu Pham () and Yakov Zinder ()
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Hanyu Gu: University of Technology Sydney
Hue Chi Lam: University of Technology Sydney
Thi Thanh Thu Pham: University of Technology Sydney
Yakov Zinder: University of Technology Sydney

Journal of Heuristics, 2023, vol. 29, issue 1, No 4, 139-175

Abstract: Abstract This paper considers the planning problem arising in the maintenance of a power distribution grid. Maintenance works require the corresponding parts of the grid to be shut down for the entire duration of maintenance which could range from one day to several weeks. The planning specifies the starting times of the required outages for maintenance and should take into account the constrained resources as well as the uncertainty involved in the maintenance works which is characterized by the risk values provided by the grid operator. The problem was presented by the French company Réseau de Transport d’Électricité for the 2020 ROADEF/EURO challenge. Several approaches were developed during the competition and all approaches are reported in this paper. We evaluate our approaches on the benchmark instances proposed for the competition. It is reported that the iterated local search metaheuristic with self-adaptive perturbation performed the best.

Keywords: Iterated local search; Large neighborhood search; Quantile minimization; Grid maintenance planning; 2020 ROADEF/EURO challenge (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10732-022-09508-1

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