Approximation Algorithms

Integrated Optimization of Timetabling and Electric Vehicle Scheduling: A Case Study of Aachen, Germany

  • Vladimir Stadnichuk
  • Jenny Segschneider
  • Arie M.C.A. Koster
  • Grit Walther
    • Categories Applications - OR and Management Sciences, Approximation Algorithms, Transportation Tags , , , ,

    We tackle the integrated planning problem of periodic timetabling and electric vehicle scheduling, crucial for cities transitioning to electric bus fleets. Given existing timetables, we allow only minor modifications and propose an iterative solution approach that addresses the Electric Vehicle Scheduling Problem (EVSP) in each iteration. Due to the NP-hard nature of EVSP, we employ … Read more

    Robust combinatorial optimization problems with knapsack constraints under interdiction uncertainty

  • Alejandro Crema
    • Categories Approximation Algorithms, Combinatorial Optimization, Robust Optimization Tags , , , ,

    We present an algorithm for finding near-optimal solutions to robust combinatorial optimization problems with knapsack constraints under interdiction uncertainty. We incorporate a heuristic for generating feasible solutions in a standard row generation approach. Experimental results are presented for set covering, simple plant location, and min-knapsack problems under a discrete-budgeted interdiction uncertainty set introduced in this … Read more

    Local Convergence Analysis for Nonisolated Solutions to Derivative-Free Methods of Optimization

  • Dat Tran
    • Categories Approximation Algorithms, Nonlinear Optimization, Unconstrained Optimization

    This paper provides a local convergence analysis for newly developed derivative-free methods in problems of smooth nonconvex optimization. We focus here on local convergence to local minimizers, which might be nonisolated and hence more challenging for convergence analysis. The main results provide efficient conditions for local convergence to arbitrary local minimizers under the fulfillment of … Read more

    Computational Methods for the Household Assignment Problem

  • Ulf Friedrich
  • Lucas Moschen
  • Ralf Münnich
  • Martin Schmidt
    • Categories Applications - OR and Management Sciences, Approximation Algorithms, Integer Programming Tags , , , ,

    We consider the household assignment problem as it occurs in the geo-referencing step of spatial microsimulation models. The resulting model is a maximum weight matching problem with additional side constraints. For real-world instances such as the one for the city of Trier in Germany, the number of binary variables exceeds 10^9, and the resulting instances … Read more

    A General Framework for Sequential Batch-Testing

  • Rayen Tan
  • Alex Xu
  • Viswanath Nagarajan
    • Categories Approximation Algorithms, Combinatorial Optimization

    \(\) We consider sequential testing problems that involve a system of \(n\) stochastic components, each of which is either working or faulty with independent probability. The overall state of the system is a function of the state of its individual components, and the goal is to determine the system state by testing its components at … Read more

    Globally Convergent Derivative-Free Methods in Nonconvex Optimization with and without Noise

  • Dat Tran
    • Categories Approximation Algorithms, Global Optimization Applications, Unconstrained Optimization

    This paper addresses the study of nonconvex derivative-free optimization problems, where only information of either smooth objective functions or their noisy approximations is available. General derivative-free methods are proposed for minimizing differentiable (not necessarily convex) functions with globally Lipschitz continuous gradients, where the accuracy of approximate gradients is interacting with stepsizes and exact gradient values. … Read more

    Maximizing a Monotone Submodular Function Under an Unknown Knapsack Capacity

  • Sabine Münch
  • Sven de Vries
    • Categories Approximation Algorithms, Combinatorial Optimization Tags , , ,

    Consider the problem of maximizing a monotone-increasing submodular function defined on a set of weighted items under an unknown knapsack capacity. Assume that items are packed sequentially into the knapsack and that the capacity of the knapsack is accessed through an oracle that answers whether an item fits into the currently packed knapsack. If an … Read more

    Solving Hard Bi-objective Knapsack Problems Using Deep Reinforcement Learning

  • Sasan Mahmoudinazlou
  • Hadi Charkhgard
  • Ali Eshragh
    • Categories Approximation Algorithms, Integer Programming Tags , , ,

    We study a class of bi-objective integer programs known as bi-objective knapsack problems (BOKPs). Our research focuses on the development of innovative exact and approximate solution methods for BOKPs by synergizing algorithmic concepts from two distinct domains: multi-objective integer programming and (deep) reinforcement learning. While novel reinforcement learning techniques have been applied successfully to single-objective … Read more

    The alternating simultaneous Halpern-Lions-Wittmann-Bauschke algorithm for finding the best approximation pair for two disjoint intersections of convex sets

  • Yair Censor
  • Rafiq Mansour
  • Daniel Reem
    • Categories Approximation Algorithms, Constrained Nonlinear Optimization, Convex Optimization Tags , , , , ,

    Given two nonempty and disjoint intersections of closed and convex subsets, we look for a best approximation pair relative to them, i.e., a pair of points, one in each intersection, attaining the minimum distance between the disjoint intersections. We propose an iterative process based on projections onto the subsets which generate the intersections. The process … Read more

    Approximation Algorithms for Min-max-min Robust Optimization and K-Adaptability under Objective Uncertainty

  • Jannis Kurtz
    • Categories Approximation Algorithms, Robust Optimization Tags , , ,

    In this work we investigate the min-max-min robust optimization problem and the k-adaptability robust optimization problem for binary problems with uncertain costs. The idea of the first approach is to calculate a set of k feasible solutions which are worst-case optimal if in each possible scenario the best of the k solutions is implemented. It … Read more