Stochastic Programming

Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) problem with Uncertainties

  • Syu-Ning Johnn
  • Yiran Zhu
  • Andrés Miniguano-Trujillo
  • Akshay Gupte
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming, Transportation Tags , , , ,

    The Home Service Assignment, Routing, and Appointment scheduling (H-SARA) problem integrates the strategical fleet-sizing, tactical assignment, operational vehicle routing and scheduling subproblems at different decision levels, with a single period planning horizon and uncertainty (stochasticity) from the service duration, travel time, and customer cancellation rate. We propose a two-stage stochastic mixed-integer linear programming model for … Read more

    Practicable Robust Stochastic Optimization under Divergence Measures

  • Douglas Alem
  • Aakil Caunhye
    • Categories Robust Optimization, Stochastic Programming Tags , , , , ,

    We seek to provide practicable approximations of the two-stage robust stochastic optimization (RSO) model when its ambiguity set is constructed with an f-divergence radius. These models are known to be numerically challenging to various degrees, depending on the choice of the f-divergence function. The numerical challenges are even more pronounced under mixed-integer rst-stage decisions. In … Read more

    New Valid Inequalities and Formulation for the Static Chance-constrained Lot-Sizing Problem

  • Chuanhou Gao
  • James R. Luedtke
  • Zeyang Zhang
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , ,

    We study the static chance-constrained lot sizing problem, in which production decisions over a planning horizon are made before knowing random future demands, and the backlog and inventory variables are then determined by the demand realizations. The chance constraint imposes a service level constraint requiring that the probability that any backlogging is required should be … Read more

    A Homogeneous Predictor-Corrector Algorithm for Stochastic Nonsymmetric Convex Conic Optimization With Discrete Support

  • Baha Alzalg
  • Mohammad Alabedalhadi
    • Categories Linear, Cone and Semidefinite Programming, Stochastic Programming Tags , , , ,

    We consider a stochastic convex optimization problem over nonsymmetric cones with discrete support. This class of optimization problems has not been studied yet. By using a logarithmically homogeneous self-concordant barrier function, we present a homogeneous predictor-corrector interior-point algorithm for solving stochastic nonsymmetric conic optimization problems. We also derive an iteration bound for the proposed algorithm. … Read more

    Barrier Methods Based on Jordan-Hilbert Algebras for Stochastic Optimization in Spin Factors

  • Baha Alzalg
    • Categories Infinite Dimensional Optimization, Linear, Cone and Semidefinite Programming, Stochastic Programming Tags , , , , ,

    We present decomposition logarithmic-barrier interior-point methods based on unital Jordan-Hilbert algebras for infinite-dimensional stochastic second-order cone programming problems in spin factors. The results show that the iteration complexity of the proposed algorithms is independent on the choice of Hilbert spaces from which the underlying spin factors are formed, and so it coincides with the best … Read more

    LSOS: Line-search Second-Order Stochastic optimization methods for nonconvex finite sums

  • Daniela di Serafino
  • Nataša Krejić
  • Nataša Krklec Jerinkić
  • Marco Viola
    • Categories Nonlinear Optimization, Stochastic Programming Tags , , , ,

    We develop a line-search second-order algorithmic framework for minimizing finite sums. We do not make any convexity assumptions, but require the terms of the sum to be continuously differentiable and have Lipschitz-continuous gradients. The methods fitting into this framework combine line searches and suitably decaying step lengths. A key issue is a two-step sampling at … Read more

    Distributionally Robust Optimization with Markovian Data

  • Daniel Kuhn
  • Tobias Sutter
  • Mengmeng Li
    • Categories Robust Optimization, Stochastic Programming Tags , , ,

    We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven distributionally robust optimization model to estimate the problem’s objective function and optimal solution. By leveraging results from … Read more

    Markov Chain Sampling of Hidden Relay States for Economic Dispatch with Cascading Failures

  • John Birge
  • Arnab Sur
    • Categories (Mixed) Integer Linear Programming, Energy, Stochastic Programming Tags , , , , ,

    Independent system operators (ISO) of electric power networks aim to dispatch electricity economically while maintaining system reliability. NERC (North America Electric Reliability Council) requires the transmission network to be (N-1)-secure, i.e., to have sufficient supply to satisfy demand in the event of the failure of any single resource in the network. Such a policy is … Read more

    Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

  • Jose Blanchet
  • Daniel Kuhn
  • Viet Anh Nguyen
  • Bahar Tașkesen
  • Man-Chung Yue
    • Categories Nonlinear Systems and Least-Squares, Robust Optimization, Stochastic Programming

    Least squares estimators, when trained on a few target domain samples, may predict poorly. Supervised domain adaptation aims to improve the predictive accuracy by exploiting additional labeled training samples from a source distribution that is close to the target distribution. Given available data, we investigate novel strategies to synthesize a family of least squares estimator … Read more

    On the Value of Multistage Risk-Averse Stochastic Facility Location With or Without Prioritization

  • Xian Yu
  • Siqian Shen
    • Categories Integer Programming, Stochastic Programming Tags , , , , , ,

    We consider a multiperiod stochastic capacitated facility location problem under uncertain demand and budget in each period. Using a scenario tree representation of the uncertainties, we formulate a multistage stochastic integer program to dynamically locate facilities in each period and compare it with a two-stage approach that determines the facility locations up front. In the … Read more