multistage stochastic mixed integer programming

Globally Converging Algorithm for Multistage Stochastic Mixed-Integer Programs via Enhanced Lagrangian Cuts

  • Hanbin Yang
  • Haoxiang Yang
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , ,

    This paper proposes a globally converging cutting-plane algorithm for solving multistage stochastic mixed-integer programs with general mixed-integer state variables. We demonstrate the generation process of Lagrangian cuts and show that Lagrangian cuts capture the convex envelope of value functions on a restricted region. To approximate nonconvex value functions to exactness, we propose to iteratively add … Read more

    A new framework to generate Lagrangian cuts in multistage stochastic mixed-integer programming

  • Christian Füllner
  • Xu Andy Sun
  • Steffen Rebennack
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , , , , ,

    Based on recent advances in Benders decomposition and two-stage stochastic integer programming we present a new generalized framework to generate Lagrangian cuts in multistage stochastic mixed-integer linear programming (MS-MILP). This framework can be incorporated into decomposition methods for MS-MILPs, such as the stochastic dual dynamic integer programming (SDDiP) algorithm. We show how different normalization techniques … Read more

    Lagrangian Dual Decision Rules for Multistage Stochastic Mixed Integer Programming

  • Maryam Daryalal
  • Merve Bodur
  • James R. Luedtke
    • Categories Stochastic Programming Tags , , , ,

    Multistage stochastic programs can be approximated by restricting policies to follow decision rules. Directly applying this idea to problems with integer decisions is difficult because of the need for decision rules that lead to integral decisions. In this work, we introduce Lagrangian dual decision rules (LDDRs) for multistage stochastic mixed integer programming (MSMIP) which overcome … Read more