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

Gu, H; Lam, HC; Pham, TTT; Zinder, Y

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

Gu, H

Lam, HC Pham, TTT Zinder, Y

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Publisher:: SPRINGER
Publication Type:: Journal Article
Citation:: Journal of Heuristics, 2023, 29, (1), pp. 139-175
Issue Date:: 2023-02-01

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Field	Value	Language
dc.contributor.author	Gu, H https://orcid.org/0000-0003-2035-2583
dc.contributor.author	Lam, HC
dc.contributor.author	Pham, TTT
dc.contributor.author	Zinder, Y https://orcid.org/0000-0003-2024-8129
dc.date.accessioned	2024-03-26T01:54:31Z
dc.date.available	2024-03-26T01:54:31Z
dc.date.issued	2023-02-01
dc.identifier.citation	Journal of Heuristics, 2023, 29, (1), pp. 139-175
dc.identifier.issn	1381-1231
dc.identifier.issn	1572-9397
dc.identifier.uri	http://hdl.handle.net/10453/177155
dc.description.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.
dc.language	English
dc.publisher	SPRINGER
dc.relation.ispartof	Journal of Heuristics
dc.relation.isbasedon	10.1007/s10732-022-09508-1
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10732-022-09508-1
dc.subject	0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 0802 Computation Theory and Mathematics
dc.subject.classification	Operations Research
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4901 Applied mathematics
dc.title	Heuristics and meta-heuristic to solve the ROADEF/EURO challenge 2020 maintenance planning problem
dc.type	Journal Article
utslib.citation.volume	29
utslib.for	0102 Applied Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0802 Computation Theory and Mathematics
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/DVC (Teaching and Learning)
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2024-03-26T01:54:29Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	29
utslib.citation.issue	1

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.

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http://hdl.handle.net/10453/177155