Deep learning and hyperparameter optimization for assessing one’s eligibility for a subcutaneous implantable cardioverter-defibrillator

  • Alain Zemkoho
    • Categories Applications - OR and Management Sciences, Applications - Science and Engineering, Optimization in Data Science Tags , , ,

    In cardiology, it is standard for patients suffering from ventricular arrhythmias (the leading cause of sudden cardiac death) belonging to high risk populations to be treated using Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs). S-ICDs carry a risk of so-called T Wave Over Sensing (TWOS), which can lead to inappropriate shocks with an inherent health risk. For this … Read more

    Scheduling of healthcare professionals using Bayesian Optimization

  • Guido Lagos
  • Francisco Jara-Moroni
    • Categories Applications - OR and Management Sciences, Scheduling, Stochastic Programming Tags , , ,

    In this paper we present a Bayesian optimization framework that iteratively “learns” good schedules for healthcare professionals of outpatient healthcare in a hospital, that minimize the overall number of patients in queue — we understand that a patient in schedule is one in queue. The hospital has several medical specialties and each is modeled as … Read more

    Stochastic Programming Models for a Fleet Sizing and Appointment Scheduling Problem with Random Service and Travel Times

  • Shutian Li
  • Karmel S. Shehadeh
  • Man Yiu Tsang
    • Categories Applications - OR and Management Sciences, Scheduling, Stochastic Programming Tags , , , ,

    We propose a new stochastic mixed-integer linear programming model for a home service fleet sizing and appointment scheduling problem (HFASP) with random service and travel times. Specifically, given a set of providers and a set of geographically distributed customers within a service region, our model solves the following decision problems simultaneously: (i) a fleet sizing … Read more

    Iteration Complexity of Fixed-Step Methods by Nesterov and Polyak for Convex Quadratic Functions

  • Melinda Hagedorn
  • Florian Jarre
    • Categories Convex Optimization, Unconstrained Optimization Tags , ,

    This note considers the momentum method by Polyak and the accelerated gradient method by Nesterov, both without line search but with fixed step length applied to strictly convex quadratic functions assuming that exact gradients are used and appropriate upper and lower bounds for the extreme eigenvalues of the Hessian matrix are known. Simple 2-d-examples show … Read more

    Subsampled cubic regularization method for finite-sum minimization

  • Max L. N. Gonçalves
    • Categories Global Optimization, Nonlinear Optimization Tags , ,

    This paper proposes and analyzes  a  subsampled Cubic Regularization Method  (CRM) for solving  finite-sum optimization problems.  The new method uses  random subsampling techniques  to approximate  the  functions, gradients and Hessians in order to reduce the overall computational cost of the CRM. Under suitable hypotheses,  first- and second-order  iteration-complexity bounds and global convergence analyses  are presented. … Read more

    Insertion Heuristics for a Class of Dynamic Vehicle Routing Problems

  • Adam N. Letchford
    • Categories Combinatorial Optimization, Transportation Tags ,

    We consider a simple family of dynamic vehicle routing problems, in which we have a fixed fleet of identical vehicles, and customer requests arrive during the route-planning process. For this kind of problem, it is natural to use an insertion heuristic. We test several such heuristics computationally, on two different variants of the problem. It … Read more

    A polyhedral study of multivariate decision trees

  • Carla Michini
  • Zachary Zhou
    • Categories (Mixed) Integer Linear Programming, Data Science Theory, Polyhedra Tags , ,

    Decision trees are a widely used tool for interpretable machine learning. Multivariate decision trees employ hyperplanes at the branch nodes to route datapoints throughout the tree and yield more compact models than univariate trees. Recently, mixed-integer programming (MIP) has been applied to formulate the optimal decision tree problem. To strengthen MIP formulations, it is crucial … Read more

    On Constrained Mixed-Integer DR-Submodular Minimization

  • Qimeng Yu
  • Simge Küçükyavuz
    • Categories (Mixed) Integer Nonlinear Programming, Polyhedra Tags , , ,

    DR-submodular functions encompass a broad class of functions which are generally non-convex and non-concave. We study the problem of minimizing any DR-submodular function, with continuous and general integer variables, under box constraints and possibly additional monotonicity constraints. We propose valid linear inequalities for the epigraph of any DR-submodular function under the constraints. We further provide … Read more

    Assigning Orders to Couriers in Meal Delivery via Integer Programming

  • Matteo Cosmi
  • Gianpaolo Oriolo
  • Veronica Piccialli
  • Paolo Ventura
    • Categories Applications - OR and Management Sciences, Integer Programming

    We investigate some optimization models for meal delivery that stem from a collaboration with an Italian company mainly operating in Rome. The focus of this company is on top-end customers, and the company pursues high Quality of Service through a careful management of delays. We then design optimization models and algorithms for dispatching orders to … Read more

    General Polyhedral Approximation of Two-Stage Robust Linear Programming

  • LukasGrunau
  • Tim Niemann
  • Sebastian Stiller
    • Categories Approximation Algorithms, Combinatorial Optimization, Robust Optimization Tags , , , ,

    We consider two-stage robust linear programs with uncertain righthand side. We develop a General Polyhedral Approximation (GPA), in which the uncertainty set $\mathcal{U}$ is substituted by a finite set of polytopes derived from the vertex set of an arbitrary polytope that dominates $\mathcal{U}$. The union of the polytopes need not contain $\mathcal{U}$. We analyse and … Read more