On optimal singular control problem for general Mckean-Vlasov differential equations: Necessary and sufficient optimality conditions

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Date

2018

Authors

Mokhtar Hafayed
Shahlar Meherrem
Saban Eren
Deniz Hasan Gucoglu

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Volume Title

Publisher

WILEY

Open Access Color

Green Open Access

Yes

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9

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2

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No
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Abstract

In this paper we derive the necessary and sufficient conditions for optimal singular control for systems governed by general controlled McKean-Vlasov differential equations in which the coefficients depend on the state of the solution process as well as of its law and control. The control domain is assumed to be convex. The control variable has 2 components ie the first being absolutely continuous and the second being singular. The proof of our result is based on the derivative of the solution process with respect to the probability law and a corresponding Ito formula. Finally an example is given to illustrate the theoretical results.

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Keywords

derivative with respect to measures, McKean-Vlasov differential equations, optimal singular control, probability measure, stochastic maximum principle, STOCHASTIC MAXIMUM PRINCIPLE, MEAN-FIELD, PARTIAL INFORMATION, SYSTEMS, DELAY, Stochastic partial differential equations (aspects of stochastic analysis), Control/observation systems governed by partial differential equations, probability measure, derivative with respect to measures, stochastic maximum principle, McKean-Vlasov differential equations, Optimal stochastic control, Optimality conditions for problems involving randomness, Vlasov equations, optimal singular control

Fields of Science

0209 industrial biotechnology, 02 engineering and technology

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OpenCitations Citation Count
13

Source

Optimal Control Applications and Methods

Volume

39

Issue

Start Page

1202

End Page

1219
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Scopus : 19

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