multistage stochastic programming

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

    On Lipschitz regularization and Lagrangian cuts in multistage stochastic mixed-integer linear programming

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

    We provide new theoretical insight on the generation of linear and non-convex cuts for value functions of multistage stochastic mixed-integer programs based on Lagrangian duality. First, we analyze in detail the impact that the introduction of copy constraints, and especially, the choice of the accompanying constraint set for the copy variable have on the properties … Read more

    A computational study of cutting-plane methods for multi-stage stochastic integer programs

  • Akul Bansal
  • Simge Küçükyavuz
    • Categories Stochastic Programming Tags , ,

    We report a computational study of cutting plane algorithms for multi-stage stochastic mixed-integer programming models with the following cuts: (i) Benders’, (ii) Integer L-shaped, and (iii) Lagrangian cuts. We first show that Integer L-shaped cuts correspond to one of the optimal solutions of the Lagrangian dual problem, and, therefore, belong to the class of Lagrangian … Read more

    Duality of upper bounds in stochastic dynamic programming

  • Bernardo Freitas Paulo da Costa
  • Vincent Leclère
    • Categories Convex Optimization, Dynamic Programming, Stochastic Programming Tags , , , ,

    For multistage stochastic programming problems with stagewise independent uncertainty, dynamic programming algorithms calculate polyhedral approximations for the value functions at each stage.  The SDDP algorithm provides piecewise linear lower bounds, in the spirit of the L-shaped algorithm, and corresponding upper bounds took a longer time to appear.  One strategy uses the primal dynamic programming recursion … Read more

    Capacity planning with uncertain endogenous technology learning

  • Tushar Rathi
  • Qi Zhang
    • Categories Applications - OR and Management Sciences, Stochastic Programming Tags , , , ,

    Optimal capacity expansion requires complex decision-making, often influenced by technology learning, which represents the reduction in expansion cost due to factors such as cumulative installed capacity. However, having perfect foresight over the technology cost reduction is highly unlikely. In this work, we develop a multistage stochastic programming framework to model capacity planning problems with endogenous … Read more

    Multistage Stochastic Fractionated Intensity Modulated Radiation Therapy Planning

  • Merve Bodur
  • Mucahit Cevik
  • Andre Augusto Cire
  • Mark Ruschin
  • Juyoung Wang
    • Categories Stochastic Programming Tags , ,

    Intensity modulated radiation therapy (IMRT) is a widely used cancer treatment technique designed to target malignant cells. To enhance its effectiveness on tumors and reduce side effects, radiotherapy plans are usually divided into consecutive treatments, or fractions, that are delivered over multiple weeks. However, typical planning approaches have focused on finding the full sequence of … Read more

    Stochastic dual dynamic programming and its variants – a review

  • Christian Füllner
  • Steffen Rebennack
    • Categories Stochastic Programming Tags , , , , , , ,

    We provide a tutorial-type review on stochastic dual dynamic programming (SDDP), as one of the state-of-the-art solution methods for large-scale multistage stochastic programs. Since introduced about 30 years ago for solving large-scale multistage stochastic linear programming problems in energy planning, SDDP has been applied to practical problems from several fields and is enriched by various … Read more

    Risk-Averse Multistage Stochastic Programs with Expected Conditional Risk Measures

  • Maryam Khatami
  • Lewis Ntaimo
  • Bernardo K. Pagnoncelli
  • Thuener Silva
    • Categories Stochastic Programming Tags , ,

    We study decomposition algorithms for risk-averse multistage stochastic programs with expected conditional risk measures (ECRMs). ECRMs are attractive because they are time-consistent, which means that a plan made today will not be changed in the future if the problem is re-solved given a realization of the random variables. We show that solving risk-averse problems based … Read more

    On the Impact of Deep Learning-based Time-series Forecasts on Multistage Stochastic Programming Policies

  • Merve Bodur
  • Mucahit Cevik
  • Juyoung Wang
    • Categories Stochastic Programming Tags , , , ,

    Multistage stochastic programming provides a modeling framework for sequential decision-making problems that involve uncertainty. One typically overlooked aspect of this methodology is how uncertainty is incorporated into modeling. Traditionally, statistical forecasting techniques with simple forms, e.g., (first-order) autoregressive time-series models, are used to extract scenarios to be added to optimization models to represent the uncertain … Read more