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A Quasi-Monte-Carlo-Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse

Author

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  • Changyin Zhou
  • Rui Su
  • Zhihui Jiang

Abstract

A two-stage stochastic quadratic programming problem with inequality constraints is considered. By quasi-Monte-Carlo-based approximations of the objective function and its first derivative, a feasible sequential system of linear equations method is proposed. A new technique to update the active constraint set is suggested. We show that the sequence generated by the proposed algorithm converges globally to a Karush-Kuhn-Tucker (KKT) point of the problem. In particular, the convergence rate is locally superlinear under some additional conditions.

Suggested Citation

  • Changyin Zhou & Rui Su & Zhihui Jiang, 2017. "A Quasi-Monte-Carlo-Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-15, August.
    • Handle: RePEc:hin:jnlmpe:1564642
    DOI: 10.1155/2017/1564642
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