2 Search Results for "Jozefowiez, Nicolas"

Document
DOI: 10.4230/LIPIcs.CP.2025.3
Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search

Authors: Valentin Antuori, Damien T. Wojtowicz, and Emmanuel Hebrard

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
The increasing hunger for remote sensing data fuels a boom in satellite imagery, leading to larger agile Earth observation satellite (AEOS) constellations. Therefore, instances of the AEOS scheduling problem (AEOSSP) has become harder to solve. As most existing approaches to solve AEOSSP are designed for a single spacecraft or smaller constellations in mind, they are not tailored to the need of our industrial partner that is about to launch a constellation of 20 AEOSs. Hence, we designed a local search solver able to schedule observations and downloads at such a scale. It relies on solving a series of sub-problems as travelling salesman problem with time windows (TSPTW), first greedily, then using a CP-SAT exact solver in order to find a solution when the greedy insertion fails. Lastly, it schedules downloads and enforces memory constraints with greedy algorithms. Experiments were carried out on instances from the literature as well as generated instances from a simulator we designed. Our experiments show that using CP to solve the sub-problem significantly improve the solutions, and overall our method is slightly better than state-of-the-art approaches.
Cite as

Valentin Antuori, Damien T. Wojtowicz, and Emmanuel Hebrard. Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 3:1-3:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{antuori_et_al:LIPIcs.CP.2025.3,
  author =	{Antuori, Valentin and Wojtowicz, Damien T. and Hebrard, Emmanuel},
  title =	{{Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{3:1--3:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.3},
  URN =		{urn:nbn:de:0030-drops-238647},
  doi =		{10.4230/LIPIcs.CP.2025.3},
  annote =	{Keywords: Local Search, Greedy Algorithms, Aerospace Applications}
}
Document
DOI: 10.4230/OASIcs.ATMOS.2013.137
Column Generation for Bi-Objective Vehicle Routing Problems with a Min-Max Objective

Authors: Boadu Mensah Sarpong, Christian Artigues, and Nicolas Jozefowiez

Published in: OASIcs, Volume 33, 13th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2013)

Abstract
Column generation has been very useful in solving single objective vehicle routing problems (VRPs). Its role in a branch-and-price algorithm is to compute a lower bound which is then used in a branch-and-bound framework to guide the search for integer solutions. In spite of the success of the method, only a few papers treat its application to multi-objective problems and this paper seeks to contribute in this respect. We study how good lower bounds for bi-objective VRPs in which one objective is a min-max function can be computed by column generation. A way to model these problems as well as a strategy to effectively search for columns are presented. We apply the ideas to two VRPs and our results show that strong lower bounds for this class of problems can be obtained in "reasonable" times if columns are intelligently managed. Moreover, the quality of the bounds obtained from the proposed model are significantly better than those obtained from the corresponding "standard" approach.
Cite as

Boadu Mensah Sarpong, Christian Artigues, and Nicolas Jozefowiez. Column Generation for Bi-Objective Vehicle Routing Problems with a Min-Max Objective. In 13th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 33, pp. 137-149, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{sarpong_et_al:OASIcs.ATMOS.2013.137,
  author =	{Sarpong, Boadu Mensah and Artigues, Christian and Jozefowiez, Nicolas},
  title =	{{Column Generation for Bi-Objective Vehicle Routing Problems with a Min-Max Objective}},
  booktitle =	{13th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{137--149},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-58-3},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{33},
  editor =	{Frigioni, Daniele and Stiller, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2013.137},
  URN =		{urn:nbn:de:0030-drops-42500},
  doi =		{10.4230/OASIcs.ATMOS.2013.137},
  annote =	{Keywords: Multi-objective optimization, column generation, integer programming, vehicle routing}
}
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