chance constraints

A Tractable Approximation of Stochastic Programming via Robust Optimization

  • Xin Chen
  • Peng Sun
  • Jiawei Zhang
  • Melvyn Sim
    • Categories Robust Optimization, Second-Order Cone Programming, Stochastic Programming Tags , , ,

    Stochastic programming, despite its immense modeling capabilities, is well known to be computationally excruciating. In this paper, we introduce a unified framework of approximating multiperiod stochastic programming from the perspective of robust optimization. Specifically, we propose a framework that integrates multistage modeling with safeguarding constraints. The framework is computationally tractable in the form of second … Read more

    Convex Approximations of Chance Constrained Programs

  • Arkadi Nemirovski
  • Alexander Shapiro
    • Categories Robust Optimization, Stochastic Programming Tags , , , ,

    We consider a chance constrained problem, where one seeks to minimize a convex objective over solutions satisfying, with a given (close to one) probability, a system of randomly perturbed convex constraints. Our goal is to build a computationally tractable approximation of this (typically intractable) problem, i.e., an explicitly given convex optimization program with the feasible … Read more

    Scenario Approximations of Chance Constraints

  • Arkadi Nemirovski
  • Alexander Shapiro
    • Categories Optimization of Simulated Systems, Stochastic Programming Tags , , , ,

    We consider an optimization problem of minimization of a linear function subject to chance constraints. In the multidimensional case this problem is, generically, a problem of minimizing under a nonconvex and difficult to compute constraints and as such is computationally intractable. We investigate the potential of conceptually simple scenario approximation of the chance constraints. The … Read more

    On complexity of stochastic programming problems

  • Arkadi Nemirovski
  • Alexander Shapiro
    • Categories Stochastic Programming Tags , , , , , , ,

    The main focus of this paper is discussion of complexity of stochastic programming problems. We argue that two-stage (linear) stochastic programming problems with recourse can be solved with a reasonable accuracy by using Monte Carlo sampling techniques, while multi-stage stochastic programs, in general, are intractable. We also discuss complexity of chance constrained problems and multi-stage … Read more