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Modified Lagrangian Methods for Separable Optimization Problems

Author

Listed:
  • Abdelouahed Hamdi
  • Aiman A. Mukheimer

Abstract

We propose a convergence analysis of a new decomposition method to solve structured optimization problems. The proposed scheme is based on a class of modified Lagrangians combined with the allocation of resources decomposition algorithm. Under mild assumptions, we show that the method generates convergent primal‐dual sequences.

Suggested Citation

  • Abdelouahed Hamdi & Aiman A. Mukheimer, 2012. "Modified Lagrangian Methods for Separable Optimization Problems," Abstract and Applied Analysis, John Wiley & Sons, vol. 2012(1).
    • Handle: RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:471854
    DOI: 10.1155/2012/471854
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    References listed on IDEAS

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    1. A. Auslender & R. Cominetti & M. Haddou, 1997. "Asymptotic Analysis for Penalty and Barrier Methods in Convex and Linear Programming," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 43-62, February.
    2. Alfred Auslender & Marc Teboulle & Sami Ben-Tiba, 1999. "Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels," Mathematics of Operations Research, INFORMS, vol. 24(3), pages 645-668, August.
    3. Alfredo N. Iusem & Marc Teboulle, 1995. "Convergence Rate Analysis of Nonquadratic Proximal Methods for Convex and Linear Programming," Mathematics of Operations Research, INFORMS, vol. 20(3), pages 657-677, August.
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