JEAN BIGEON

Dr. JEAN BIGEON

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Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 March 2021 in Computational Optimization and Applications
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JBJEAN BIGEON
JEAN BIGEON
SDSébastien Le Digabel
Sébastien Le Digabel
LSLudovic Salomon
Ludovic Salomon

16 July 2024 in Computational Optimization and Applications
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Journal Article
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JBJEAN BIGEON
JEAN BIGEON
SDSébastien Le Digabel
Sébastien Le Digabel
LSLudovic Salomon
Ludovic Salomon


12 July 2021 in Operations Research Forum
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CACharles Audet
Charles Audet
JBJEAN BIGEON
JEAN BIGEON
RCRomain Couderc
Romain Couderc

8 October 2021 in Energies
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SSSoha Saad
Soha Saad
FOFlorence Ossart
Florence Ossart
JBJEAN BIGEON
JEAN BIGEON
ESEtienne Sourdille
Etienne Sourdille
HGHarold Gance
Harold Gance
The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper proposes the use of sensitivity analysis in order to evaluate the influence of different traffic adjustment actions (e.g., spacing between trains and speed reduction) on the train supply voltage, which must never drop below the critical value prescribed by technical standards. Three global sensitivity analysis methods dedicated to black box, multivariate, nonlinear models are considered: generalized Sobol indices, energy distance-based indices, and regional sensitivity analysis. The three methods are applied to a simple traffic rescheduling test case and give similar results, but at different costs. Regional sensitivity analysis appears to be the most suitable method for the present application: it is easy to implement, rather fast, and accounts for constraints on the system output (a key feature for electrical incident management). The application of this method to a test case representative of a real rescheduling problem shows that it provides the information needed by the traffic manager to reschedule traffic in an efficient way. The same type of approach can be used for any power system optimization problem with the same characteristics.

9 August 2025 in Computational Optimization and Applications
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Journal Article
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CACharles Audet
Charles Audet
JBJEAN BIGEON
JEAN BIGEON
RCRomain Couderc
Romain Couderc
Michael KokkolarasMichael Kokkolaras
Michael Kokkolaras