Michael Saint-Guillain

Passionné par la recherche opérationnelle, Michael a lancé Rombio suite à sa thèse de doctorat en intelligence artificielle et une collaboration avec la NASA.

September 23, 2022

Michael Saint-Guillain

Passionné par la recherche opérationnelle, Michael a lancé Rombio suite à sa thèse de doctorat en intelligence artificielle et une collaboration avec la NASA.

July 4, 2016

Romie: A Domain-Independent Tool for Computer-Aided Robust Operations ManagementRomie is a decision support tool based on AI’s latest advances in the domain of robust scheduling. Unlike all its predecessors, the tool allows to (i) visually model the operational problem and context entirely (ii) optimize to find near-optimal schedules while taking uncertainty into account and deals with (iii) a combination of various key performance indicators (KPIs). It comes with a web user interface.

July 4, 2016

Probabilistic Temporal Networks with Ordinary Distributions: Theory, Robustness and Expected UtilityMost existing works in Probabilistic Simple Temporal Networks (PSTNs) base their frameworks on well-dened, parametric probability distributions. Under the operational contexts of both strong and dynamic control, this paper addresses robustness measure of PSTNs, i.e. the execution success probability, where the probability distributions of the contingent durations are ordinary, not necessarily parametric, nor symmetric (e.g. histograms, PERT), as long as these can be discretized.

July 4, 2016

Robust Operations Management on MarsWe compare both deterministic and robust stochastic approaches to the problem of scheduling a set of scientific tasks under processing time uncertainty. While dealing with strict time windows and minimum transition time constraints, we provide closed-form expressions to compute the exact probability that a solution has to remain feasible.

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