Bayesian multi-objective optimization for quantitative risk assessment in microbiology

Subhasish Basak (1, 2, 3) , Julien Bect (2, 3) , Laurent L. Guillier (1) , Fanny Tenenhaus-Aziza (4) , Janushan Christy (5) , Emmanuel Vazquez (2, 3)

1 ANSES - Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail
2 L2S - Laboratoire des signaux et systèmes
3 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
4 CNIEL - Centre National Interprofessionnel de l'Economie Laitière [Paris]
5 Actalia [La Roche sur Foron]

As a part of the European project ArtiSaneFood, the primary goal of this collaborative work between ANSES, CNIEL and L2S is to establish efficient bio-intervention strategies for cheese producers in France, in order to "economically" reduce the risk of Haemolytic Uremic Syndrome (HUS) caused by Shiga-Toxin producing Escherichia Coli (STEC) present in raw-milk soft cheese. This translates into a multi-objective optimization problem of a stochastic simulator based on a quantitative risk assessment (QRA) model proposed by Frédérique Perrin and co-authors in 2014, to estimate the Pareto optimal solutions for the process intervention parameters.

Domains: Statistics [stat]; Machine Learning [stat.ML]; Computer Science [cs]; Operations Research [cs.RO]; Life Sciences [q-bio]; Food engineering

Subhasish Basak, Julien Bect, Laurent L. Guillier, Fanny Tenenhaus-Aziza, Janushan Christy, et al.. Bayesian multi-objective optimization for quantitative risk assessment in microbiology. MASCOT-NUM 2022, Jun 2022, Clermont-Ferrand, France. . ⟨hal-03715857⟩