For a list of activities beyond my previous position at TU Berlin, see also my
- Spatiotemporal reconstruction of ancient road networks through sequential cost–benefit analysis (Maximilian J. Stahlberg, Guillaume Sagnol, Benjamin Ducke and Max Klimm)
PNAS Nexus, 2(2):pgac313, 2023.
@article{StahlbergSagnolDuckeKlimm2023,
author = {Maximilian J. Stahlberg and Guillaume Sagnol and Benjamin Ducke and Max Klimm},
title = {Spatiotemporal reconstruction of ancient road networks through sequential cost--benefit analysis},
journal = {PNAS Nexus},
year = {2023},
doi = {10.1093/pnasnexus/pgac313},
volume = {2},
number = {2},
pages = {pgac313},
}
- Fast Screening Rules for Optimal Design via Quadratic Lasso Reformulation (Guillaume Sagnol and Luc Pronzato)
Journal of Machine Learning Research, 24(307):1–32, 2023.
@article{SagnolPronzato2023,
author = {Guillaume Sagnol and Luc Pronzato},
title = {Fast Screening Rules for Optimal Design via Quadratic Lasso Reformulation},
journal = {Journal of Machine Learning Research},
year = {2023},
volume = {24},
number = {307},
pages = {1--32},
url = {http://jmlr.org/papers/v24/22-1305.html},
arxiv = {2310.08939},
}
- Competitive Kill-and-Restart and Preemptive Strategies for Non-Clairvoyant Scheduling (Sven Jäger, Guillaume Sagnol, Daniel Schmidt genannt Waldschmidt and Philipp Warode)
IPCO 2023 – Proc. 24th Conference on Integer Programming and Combinatorial Optimization, pp. 246–260.
@inproceedings{JaegerSagnolSchmidtGW2023,
arxiv = {2211.02044},
author = {Sven Jäger and Guillaume Sagnol and Daniel Schmidt genannt Waldschmidt and Philipp Warode},
title = {Competitive Kill-and-Restart and Preemptive Strategies for Non-Clairvoyant Scheduling},
year = {2023},
booktitle = {IPCO 2023 – Proc. 24th Conference on Integer Programming and Combinatorial Optimization},
pages = {246--260},
doi = {10.1007/978-3-031-32726-1_18},
series = {Lecture Notes in Computer Science (LNCS)},
volume = {13904},
}
- Improved Analysis of Two Algorithms for Min-Weighted Sum Bin Packing (Guillaume Sagnol)
IWOCA 2023 – Proc. 34th, pp. 343–355.
@inproceedings{Sagnol2023,
author = {Guillaume Sagnol},
title = {Improved Analysis of Two Algorithms for Min-Weighted Sum Bin Packing},
booktitle = {IWOCA 2023 – Proc. 34th},
series = {Lecture Notes in Computer Science (LNCS)},
volume = {13889},
year = {2023},
pages = {343--355},
doi = {10.1007/978-3-031-34347-6_29},
arxiv = {2304.02498},
}
- Surgery Scheduling in Flexible Operating Rooms by using a Convex Surrogate Model of Second-Stage Costs (Mohammed Majthoub Almoghrabi and Guillaume Sagnol)
Preprint, 2023.
@techreport{almoghrabi2023surgery,
title = {Surgery Scheduling in Flexible Operating Rooms by using a Convex Surrogate Model of Second-Stage Costs},
author = {Majthoub Almoghrabi, Mohammed and Sagnol, Guillaume},
year = {2023},
arxiv = {2304.13670},
}
We study the elective surgery planning problem in a hospital with operation rooms shared by elective and emergency patients. This problem can be split in two distinct phases. First, a subset of patients to be operated in the next planning period has to be selected, and the selected patients have to be assigned to a block and a tentative starting time. Then, in the online phase of the problem, a policy decides how to insert the emergency patients in the schedule and may cancel planned surgeries. The overall goal is to minimize the expectation of a cost function representing the assignment of patient to blocks, case cancellations, overtime, waiting time and idle time. We model the offline problem by a two-stage stochastic program, and show that the second-stage costs can be replaced by a convex piecewise linear surrogate model that can be computed in a preprocessing step. This results in a mixed integer program which can be solved in a short amount of time, even for very large instances of the problem. We also describe a greedy policy for the online phase of the problem, and analyze the performance of our approach by comparing it to either heuristic methods or approaches relying on sampling average approximation (SAA) on a large set of benchmarking instances. Our simulations indicate that our approach can reduce the expected costs by as much as 20% compared to heuristic methods and is able to solve problems with 1000 patients in about one minute, while SAA-approaches fail to obtain near-optimal solutions within 30 minutes, already for 100 patients.
- PICOS: A Python interface to conic optimization solvers (Guillaume Sagnol and Maximilian Stahlberg)
J. Open Source Softw., 7(70):3915, 2022.
@article{SagnolStahlberg2022,
author = {Sagnol, Guillaume and Stahlberg, Maximilian},
title = {{PICOS}: A Python interface to conic optimization solvers},
journal = {J. Open Source Softw.},
year = {2022},
volume = {7},
number = {70},
pages = {3915},
doi = {10.21105/joss.03915},
}
- Competitive Algorithms for Symmetric Rendezvous on the Line (Max Klimm, Guillaume Sagnol, Martin Skutella and Khai Van Tran)
SODA 2022 – Proc. 33rd ACM-SIAM Symposium on Discrete Algorithms, pp. 329–347.
@inproceedings{KlimmSagnolSkutella+2022,
author = {Klimm, Max and Sagnol, Guillaume and Skutella, Martin and Van Tran, Khai},
booktitle = {SODA 2022 – Proc. 33rd ACM-SIAM Symposium on Discrete Algorithms},
title = {Competitive Algorithms for Symmetric Rendezvous on the Line},
doi = {10.1137/1.9781611977073.16},
pages = {329--347},
year = {2022},
url = {https://epubs.siam.org/doi/reader/10.1137/1.9781611977073.16},
}
- Improved Bounds for Stochastic Extensible Bin Packing under Distributional Assumptions (Guillaume Sagnol and Daniel Schmidt genannt Waldschmidt)
ISCO 2022 – Proc. 7th International Symposium on Combinatorial Optimization, pp. 228–241.
@inproceedings{SagnolSchmidtGW22,
title = {Improved Bounds for Stochastic Extensible Bin Packing under Distributional Assumptions},
author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel},
booktitle = {ISCO 2022 – Proc. 7th International Symposium on Combinatorial Optimization},
year = {2022},
doi = {10.1007/978-3-031-18530-4_17},
series = {Lecture Notes in Computer Science},
volume = {13526},
pages = {228--241},
arxiv = {2002.00060},
}
- Removing inessential points in $c-$ and $A-$optimal design (Luc Pronzato and Guillaume Sagnol)
J. Stat. Plan. Inference, 213:233–252, 2021.
@article{PronzatoSagnol2021,
author = {Pronzato, Luc and Sagnol, Guillaume},
title = {Removing inessential points in $c-$ and $A-$optimal design},
journal = {J. Stat. Plan. Inference},
year = {2021},
doi = {10.1016/j.jspi.2020.11.011},
volume = {213},
pages = {233--252},
url = {https://hal.science/hal-02868664},
}
- Restricted Adaptivity in Stochastic Scheduling (Guillaume Sagnol and Daniel Schmidt genannt Waldschmidt)
ESA 2021 – Proc. 29th European Symposium on Algorithms, pp. 79:1–79:14.
@inproceedings{SagnolSchmidtGW21,
author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel},
title = {{Restricted Adaptivity in Stochastic Scheduling}},
booktitle = {ESA 2021 – Proc. 29th European Symposium on Algorithms},
pages = {79:1--79:14},
series = {LIPIcs},
year = {2021},
volume = {204},
doi = {10.4230/LIPIcs.ESA.2021.79},
arxiv = {2106.15393},
}
- An algorithm based on Semidefinite Programming for finding minimax optimal designs (Belmiro P.M. Duarte, Guillaume Sagnol and Weng Kee Wong)
Comput. Stat. Data Anal., 119:99–117, 2018.
@article{DuarteSagnolWong2018,
author = {Duarte, Belmiro P.M. and Sagnol, Guillaume and Wong, Weng Kee},
title = {An algorithm based on Semidefinite Programming for finding minimax optimal designs},
journal = {Comput. Stat. Data Anal.},
volume = {119},
pages = {99--117},
year = {2018},
doi = {10.1016/j.csda.2017.09.008},
url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-66249},
}
- The Cone of Flow Matrices: Approximation Hierarchies and Applications (Guillaume Sagnol, Marco Blanco and Thibault Sauvage)
Networks, 72(1):128–150, 2018.
Extended abstract appeared in Proc. of INOC 2017
@article{SagnolBlancoSauvage2018,
author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibault},
title = {The Cone of Flow Matrices: Approximation Hierarchies and Applications},
journal = {Networks},
doi = {10.1002/net.21820},
year = {2018},
volume = {72},
number = {1},
pages = {128--150},
url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-64399},
}
- Robust allocation of operating rooms: A cutting plane approach to handle lognormal case durations (Guillaume Sagnol, Christoph Barner, Ralf Borndörfer, Mickaël Grima, Matthes Seeling, Claudia Spies and Klaus Wernecke)
Eur. J. Oper. Res., 271(2):420–435, 2018.
@article{SagnolBarnerBorndoerferetal.2018,
title = {Robust allocation of operating rooms: A cutting plane approach to handle lognormal case durations},
journal = {Eur. J. Oper. Res.},
year = {2018},
volume = {271},
number = {2},
pages = {420--435},
doi = {10.1016/j.ejor.2018.05.022},
author = {Sagnol, Guillaume and Barner, Christoph and Bornd{\"o}rfer, Ralf and Grima, Micka{\"e}l and Seeling, Matthes and Spies, Claudia and Wernecke, Klaus},
url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-58502},
}
- Approximation Hierarchies for the Cone of Flow Matrices (Guillaume Sagnol, Marco Blanco and Thibault Sauvage)
INOC 2017 – Proc. 8th International Network Optimization Conference, pp. 275 – 284.
@inproceedings{SagnolBlancoSauvageInoc2017,
title = {Approximation Hierarchies for the Cone of Flow Matrices},
author = {Sagnol, Guillaume and Blanco, Marco and Sauvage, Thibault},
year = {2018},
booktitle = {INOC 2017 – Proc. 8th International Network Optimization Conference},
volume = {64},
pages = {275 -- 284},
doi = {10.1016/j.endm.2018.02.002},
series = {Electron. Notes Discret. Math.},
url = {https://nbn-resolving.org/urn:nbn:de:0297-zib-64399},
}
- The Price of Fixed Assignments in Stochastic Extensible Bin Packing (Guillaume Sagnol, Daniel Schmidt genannt Waldschmidt and Alexander Tesch)
WAOA 2018 – Proc. 16th Workshop on Approximation and Online Algorithms, pp. 327–347.
@inproceedings{SagnolSchmidtGWTesch2018,
title = {The Price of Fixed Assignments in Stochastic Extensible Bin Packing},
year = {2018},
author = {Sagnol, Guillaume and Schmidt genannt Waldschmidt, Daniel and Tesch, Alexander},
booktitle = {WAOA 2018 – Proc. 16th Workshop on Approximation and Online Algorithms},
volume = {11312},
pages = {327--347},
doi = {10.1007/978-3-030-04693-4_20},
arxiv = {2002.00060},
}