Applications – Science and Engineering

An Improved Penalty Algorithm using Model Order Reduction for MIPDECO problems with partial observations

  • Dominik Garmatter
  • Margherita Porcelli
  • Francesco Rinaldi
  • Martin Stoll
    • Categories (Mixed) Integer Nonlinear Programming, Optimization of Systems modeled by PDEs Tags , , , ,

    This work addresses optimal control problems governed by a linear time-dependent partial differential equation (PDE) as well as integer constraints on the control. Moreover, partial observations are assumed in the objective function. The resulting problem poses several numerical challenges due to the mixture of combinatorial aspects, induced by integer variables, and large scale linear algebra … Read more

    Data-Driven Ranges of Near-Optimal Actions for Finite Markov Decision Processes

  • Wesley Marrero
  • Mariel S. Lavieri
  • Ambuj Tewari
  • Jeremy Sussman
  • Rodney A. Hayward
    • Categories Applications - OR and Management Sciences, Applications - Science and Engineering, Dynamic Programming Tags , , , , ,

    Markov decision process (MDP) models have been used to obtain non-stationary optimal decision rules in various applications, such as treatment planning in medical decision making. However, in practice, decision makers may prefer other strategies that are not statistically different from the optimal decision rules. To benefit from the decision makers’ expertise and provide flexibility in … Read more

    Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems

  • Tommaso Giovannelli
  • Griffin D. Kent
  • Luis Nunes Vicente
    • Categories Data-Mining, Nonlinear Optimization, Stochastic Programming Tags , , ,

    Two-level stochastic optimization formulations have become instrumental in a number ofmachine learning contexts such as continual learning, neural architecture search, adversariallearning, and hyperparameter tuning. Practical stochastic bilevel optimization problemsbecome challenging in optimization or learning scenarios where the number of variables ishigh or there are constraints. In this paper, we introduce a bilevel stochastic gradient method … Read more

    Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach

  • Dimitris Bertsimas
  • Ryan Cory-Wright
  • Nicholas A. G. Johnson
    • Categories Applications - OR and Management Sciences, Data-Mining, Statistics Tags , , , ,

    We study the Sparse Plus Low-Rank decomposition problem (SLR), which is the problem of decomposing a corrupted data matrix into a sparse matrix of perturbations plus a low-rank matrix containing the ground truth. SLR is a fundamental problem in Operations Research and Machine Learning which arises in various applications, including data compression, latent semantic indexing, … Read more

    Comparing Solution Paths of Sparse Quadratic Minimization with a Stieltjes Matrix

  • Ziyu He
  • Shaoning Han
  • Andrés Gómez
  • Ying Cui
  • Jong-Shi Pang
    • Categories Nonsmooth Optimization, Quadratic Programming, Statistics Tags , , ,

    This paper studies several solution paths of sparse quadratic minimization problems as a function of the weighing parameter of the bi-objective of estimation loss versus solution sparsity. Three such paths are considered: the “L0-path” where the discontinuous L0-function provides the exact sparsity count; the “L1-path” where the L1-function provides a convex surrogate of sparsity count; … Read more

    Approximate Dynamic Programming for Crowd-shipping with In-store Customers

  • Kianoush Mousavi
  • Merve Bodur
  • Mucahit Cevik
  • Matthew J. Roorda
    • Categories Civil and Environmental Engineering, Dynamic Programming, Transportation Tags , , , ,

    Crowd-shipping has gained significant attention as a last-mile delivery option over the recent years. In this study, we propose a variant of dynamic crowd-shipping model with in-store customers as crowd-shippers to deliver online orders within few hours. We formulate the problem as a Markov decision process and develop an approximate dynamic programming (ADP) policy using … Read more

    Applications of stochastic mixed-integer second-order cone optimization

  • Baha Alzalg
  • Hadjer Alioui
    • Categories (Mixed) Integer Nonlinear Programming, Applications - Science and Engineering, Second-Order Cone Programming Tags , , ,

    Second-order cone programming problems are a tractable subclass of convex optimization problems and there are known polynomial algorithms for solving them. Stochastic second-order cone programming problems have also been studied in the past decade and efficient algorithms for solving them exist. A new class of interest to optimization community and practitioners is the mixed-integer version … Read more

    Nonlinear matrix recovery using optimization on the Grassmann manifold

  • Coralia Cartis
  • Armin Eftekhari
  • Florentin Goyens
    • Categories Applications - Science and Engineering, Constrained Nonlinear Optimization Tags , , ,

    We investigate the problem of recovering a partially observed high-rank matrix whose columns obey a nonlinear structure such as a union of subspaces, an algebraic variety or grouped in clusters. The recovery problem is formulated as the rank minimization of a nonlinear feature map applied to the original matrix, which is then further approximated by … Read more

    Determining locations and layouts for parcel lockers to support supply chain viability at the last mile

  • Michael Kahr
    • Categories (Mixed) Integer Linear Programming, Facility Planning and Design, Transportation Tags , , , ,

    The pandemic caused by the corona virus SARS-CoV-2 raised many new challenges for humanity. For instance, governments imposed regulations such as lockdowns, resulting in supply chain shocks at different tiers. Additionally, delivery services reached their capacity limits because the demand for mail orders soared temporarily during the lockdowns. We argue that one option to support … Read more

    Linearizing Bilinear Products of Shadow Prices and Dispatch Variables in Bilevel Problems for Optimal Power System Planning

  • Grani A. Hanasusanto
  • Nicholas Laws
    • Categories Applications - OR and Management Sciences, Applications - Science and Engineering, Energy Tags , , , ,

    This work presents a general method for linearizing bilinear terms in the upper level of bilevel optimization problems when the bilinear terms are products of the primal and dual variables of the lower level. Bilinear terms of this form often appear in energy market optimization models where the dual variable represents the market price of … Read more