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Journal Articles Applied Mathematics and Optimization Year : 2023

Decomposition of convex high dimensional aggregative stochastic control problems

Abstract

We consider the framework of convex high dimensional stochastic control problems, in which the controls are aggregated in the cost function. As first contribution, we introduce a modified problem, whose optimal control is under some reasonable assumptions an ε-optimal solution of the original problem. As second contribution, we present a decentralized algorithm whose convergence to the solution of the modified problem is established. Finally, we study the application of the developed tools in an engineering context, studying a coordination problem for large populations of domestic thermostatically controlled loads (TCLs).
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Dates and versions

hal-02917014 , version 1 (18-08-2020)
hal-02917014 , version 2 (18-08-2020)
hal-02917014 , version 3 (17-09-2020)
hal-02917014 , version 4 (20-10-2021)
hal-02917014 , version 5 (02-03-2023)

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Adrien Seguret, Clémence Alasseur, Joseph Frédéric Bonnans, Antonio de Paola, Nadia Oudjane, et al.. Decomposition of convex high dimensional aggregative stochastic control problems. Applied Mathematics and Optimization, 2023, 88 (8), pp.35. ⟨10.1007/s00245-023-09977-1⟩. ⟨hal-02917014v5⟩
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