Alvaro Maggiar

Multi-Echelon Inventory Management for a Non-Stationary Capacitated Distribution Network

  • Alvaro Maggiar
  • Irene Song
  • Alp Muharremoglu
    • Categories Applications - OR and Management Sciences, Dynamic Programming, Supply Chain Management Tags , ,

    We present an inventory management solution for a non-stationary capacitated multi-echelon distribution network involving thousands of products. Assuming backlogged sales, we revisit and leverage the seminal multi-echelon inventory management results in the literature to establish the structural properties of the problem, and derive an efficient and practical solution method. In particular, we describe how the … Read more

    Joint Inventory and Revenue Management with Removal Decisions

  • Alvaro Maggiar
  • Ali Sadighian
    • Categories Applications - OR and Management Sciences, Dynamic Programming, Supply Chain Management Tags , , , , , ,

    We study the problem of a retailer that maximizes profit through joint replenishment, pricing and removal decisions. This problem is motivated by the observation that retailers usually retain rights to remove inventory from their network either by returning it to the suppliers or through liquidation in the face of random demand and capacity constraints. We … Read more

    Sample Average Approximation with Adaptive Importance Sampling

  • Mingbin Feng
  • Alvaro Maggiar
  • Jeremy Staum
  • Andreas Wächter
    • Categories Stochastic Programming Tags , , , ,

    We study sample average approximations under adaptive importance sampling in which the sample densities may depend on previous random samples. Based on a generic uniform law of large numbers, we establish uniform convergence of the sample average approximation to the true function. We obtain convergence of the optimal value and optimal solutions of the sample … Read more

    Uniform Convergence of Sample Average Approximation with Adaptive Importance Sampling

  • Mingbin Feng
  • Alvaro Maggiar
  • Jeremy Staum
  • Andreas Wächter
    • Categories Stochastic Programming Tags , , , ,

    We study sample average approximations under adaptive importance sampling. Based on a Banach-space-valued martingale strong law of large numbers, we establish uniform convergence of the sample average approximation to the function being approximated. In the optimization context, we obtain convergence of the optimal value and optimal solutions of the sample average approximation. Citation Technical Report … Read more

    A Derivative-Free Trust-Region Algorithm for the Optimization of Functions Smoothed via Gaussian Convolution Using Adaptive Multiple Importance Sampling

  • Irina S Dolinskaya
  • Alvaro Maggiar
  • Jeremy Staum
  • Andreas Wächter
    • Categories Nonlinear Optimization

    In this paper we consider the optimization of a functional $F$ defined as the co nvolution of a function $f$ with a Gaussian kernel. We propose this type of objective function for the optimization of the output of complex computational simulations, which often present some form of deterministic noise and need to be smoothed for … Read more