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Solving infinite-dimensional optimizaiton problems by polynomial approximation

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  • DEVOLDER, Olivier
  • GLINEUR, François
  • NESTEROV, Yurii

Abstract

In this paper, we solve a class of convex infinite-dimensional optimization problems using a numerical approximation method that does not rely on discretization. Instead, we restrict the decision variable to a sequence of finite-dimensional linear subspaces of the original infinite-dimensional space and solve the corresponding finite-dimensional problems in a efficient way using structured convex optimization techniques. We prove that, under some reasonable assumptions, the sequence of these optimal values converges to the optimal value of the original infinite-dimensional problem and give an explicit description of the corresponding rate of convergence.
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Suggested Citation

  • DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2010. "Solving infinite-dimensional optimizaiton problems by polynomial approximation," LIDAM Reprints CORE 2241, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvrp:2241
    Note: In : M. Diehl, F. Glineur, E. Jarlebring and W. Michiels (eds.), Recent Advances in Optimization and its Applications in ENgineering, Heidelberg, Springer, 37-46, 2010
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    References listed on IDEAS

    as
    1. NESTEROV, Yu., 2000. "Squared functional systems and optimization problems," LIDAM Reprints CORE 1472, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Pierre-Philippe Combes & Thierry Mayer & Jacques-François Thisse, 2008. "Economic Geography: The Integration of Regions and Nations," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00311000, HAL.
    3. Huriot,Jean-Marie & Thisse,Jacques-François (ed.), 2009. "Economics of Cities," Cambridge Books, Cambridge University Press, number 9780521118279, October.
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    Cited by:

    1. Jubril, A.M. & Olaniyan, O.A. & Komolafe, O.A. & Ogunbona, P.O., 2014. "Economic-emission dispatch problem: A semi-definite programming approach," Applied Energy, Elsevier, vol. 134(C), pages 446-455.
    2. Kristina Rognlien Dahl, 2019. "A convex duality approach for pricing contingent claims under partial information and short selling constraints," Papers 1902.10492, arXiv.org.
    3. Kristina Rognlien Dahl, 2019. "Management of a hydropower system via convex duality," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(1), pages 43-71, February.

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