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From the 1 of 10 linked papers with an AI index.

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10 papers

math.OC2026

Optimal Control of Pandemic Dynamics via Model Predictive Control: A Health-Economic Trade-off Analysis

Lokman Rachid Melhani, Lars Grune, Antonino Sferlazza +3

The paper proposes a model predictive control framework applied to an extended SEIR-V model to optimally balance disease mitigation and economic impact, showing that the resulting…

math.DS2026

Structure preserving properties of higher order moment closures for TASEP

Kilian Pioch, Lars Grüne, Thomas Kriecherbauer +1

The totally asymmetric simple exclusion process (TASEP) is a stochastic model for the unidirectional flow of interacting particles on a 1D-lattice that is much used in systems biol…

math.OC2026

Stability and performance of stochastic economic MPC -- Stochastic characterization of the closed-loop asymptotics

Jonas Schießl, Hannah Selder, Ruchuan Ou +3

Model Predictive Control (MPC) is well understood in the deterministic setting, yet rigorous stability and performance guarantees for stochastic MPC remain limited to the considera…

math.OC2026

A Nine-Compartment Nonlinear Epidemic Model with Spline-Based Identification of Time-Varying Transmission and Vaccination Dynamics: Application to the COVID-19 Third Wave in Italy

Lokman Rachid Melhani, Antonino Sferlazza, Lars Grüne +6

We develop a nine-compartment nonlinear epidemic model incorporating two co-circulating viral strains (ancestral I1 and the Alpha variant B.1.1.7 I2, which is 43-90% more transmiss…

math.OC2026

Decaying Sensitivity of the Zero Solution for a Class of Nonlinear Optimal Control Problems

Lars Grüne, Mario Sperl

We study spatial decay properties of sensitivities in a nonlinear optimal control problem with a graph-structured interaction topology. For a problem with nonlinear decoupled dynam…

math.OC2026

Closed-loop analysis of linear stochastic MPC with risk-averse constraints

Jonas Schießl, Ruchuan Ou, Michael H. Baumann +2

Chance constraints are widely used in stochastic model predictive control (MPC) to enforce probabilistic state and input constraints in the presence of unbounded disturbances. Howe…