Double smoothing technique for infinite-dimensional optimization problems with applications to optimal control
Olivier Devolder (),
François Glineur and
Yurii Nesterov ()
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Olivier Devolder: Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium
Yurii Nesterov: Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium
No 2010034, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
Abstract:
In this paper, we propose an efficient technique for solving some infinite-dimensional problems over the sets of functions of time. In our problem, besides the convex point-wise constraints on state variables, we have convex coupling constraints with finite-dimensional image. Hence, we can formulate a finite-dimensional dual problem, which can be solved by efficient gradient methods. We show that it is possible to reconstruct an approximate primal solution. In order to accelerate our schemes, we apply double-smoothing technique. As a result, our method has complexity O (1/[epsilon] ln 1/[epsilon]) gradient iterations, where [epsilon] is the desired accuracy of the solution of the primal-dual problem. Our approach covers, in particular, the optimal control problems with trajectory governed by a system of ordinary differential equations. The additional requirement could be that the trajectory crosses in certain moments of time some convex sets.
Keywords: convex optimization; optimal control; fast gradient methods; complexity bounds; smoothing technique (search for similar items in EconPapers)
Date: 2010-07-01
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2010034
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