Applications – OR and Management Sciences

An enhanced mathematical model for optimal simultaneous preventive maintenance scheduling and workshop planning

  • Gabrijela Obradović
  • Ann-Brith Strömberg
    • Categories (Mixed) Integer Linear Programming, Multi-Criteria Optimization, Scheduling

    For a system to stay operational, maintenance of its components is required and to maximize the operational readiness of a system, preventive maintenance planning is essential. There are two stakeholders—a system operator and a maintenance workshop—and a contract regulating their joint activities. Each contract leads to a bi-objective optimization problem. Components that require maintenance are … Read more

    Healthcare Operations Research and Management under Pandemics: a Review

  • Majid Salavati-Khoshghalb
    • Categories Applications - OR and Management Sciences Tags , , , , , ,

    This literature review sought to identify the role of Operations Research and Management (OR-and-OM) in the Healthcare Systems (HS) decision/policy making processes that have undergone a remarkable transformation when faced with pandemics, especially during the COVID-19 era. In this study, we investigate OR models and OM techniques that facilitate clinical decision-making with short- and long-term … Read more

    Resilient Relay Logistics Network Design: A k-Shortest Path Approach

  • Onkar Anand Kulkarni
  • Mathieu Dahan
    • Categories (Mixed) Integer Linear Programming, Facility Planning and Design, Production and Logistics Tags , , , ,

    Problem definition: We study the problem of designing large-scale resilient relay logistics hub networks. We propose a model of k-Shortest Path Network Design, which aims to improve a network’s efficiency and resilience through its topological configuration, by locating relay logistics hubs to connect each origin-destination pair with k paths of minimum lengths, weighted by their … Read more

    Conjecturing-Based Discovery of Patterns in Data

  • J. Paul Brooks
  • David Edwards
  • C. E. Larson
  • Nico Van Cleemput
    • Categories Applications - OR and Management Sciences, Data Science Algorithms, Optimization in Data Science Tags , , , ,

    We propose the use of a conjecturing machine that suggests feature relationships in the form of bounds involving nonlinear terms for numerical features and boolean expressions for categorical features. The proposed Conjecturing framework recovers known nonlinear and boolean relationships among features from data. In both settings, true underlying relationships are revealed. We then compare the … Read more

    DeLuxing: Deep Lagrangian Underestimate Fixing for Column-Generation-Based Exact Methods

  • Yu Yang
    • Categories Branch and Cut Algorithms, Integer Programming, Transportation

    In this paper, we propose an innovative variable fixing strategy called deep Lagrangian underestimate fixing (DeLuxing). It is a highly effective approach for removing unnecessary variables in column-generation (CG)-based exact methods used to solve challenging discrete optimization problems commonly encountered in various industries, including vehicle routing problems (VRPs). DeLuxing employs a novel linear programming (LP) … Read more

    A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing

  • Leonardo Lozano
  • Juan Borrero
    • Categories Applications - OR and Management Sciences, Network Optimization, Stochastic Programming Tags , , ,

    We consider linear combinatorial optimization problems under uncertain disruptions that increase the cost coefficients of the objective function. A decision-maker, or planner, can invest resources to probe the components (i.e., the coefficients) in order to learn their disruption status. In the proposed probing optimization problem, the planner, knowing just the disruptions’ probabilities, selects which components … Read more

    Optimal Multi-Agent Pickup and Delivery Using Branch-and-Cut-and-Price

  • Edward Lam
    • Categories Branch and Cut Algorithms, Integer Programming, Transportation

    Given a set of agents and a set of pickup-delivery requests located on a two-dimensional map, the Multi-Agent Pickup and Delivery problem assigns the requests to the agents such that every agent moves from its start location to the locations of its assigned requests and finally to its end location without colliding into any other … Read more

    Data-Driven Counterfactual Optimization For Personalized Clinical Decision-Making

  • Che-Yi Liao
  • Esmaeil Keyvanshokooh
  • Gian-Gabriel Garcia
    • Categories Applications - OR and Management Sciences, Optimization in Data Science Tags , , , ,

    Chronic diseases have a significant impact on global mortality rates and healthcare costs. Notably, machine learning-based clinical assessment tools are becoming increasingly popular for informing treatment targets for high-risk patients with chronic diseases. However, using these tools alone, it is challenging to identify personalized treatment targets that lower the risks of adverse outcomes to a … Read more

    Improving the Security of United States Elections with Robust Optimization

  • Bradley Sturt
    • Categories Applications - OR and Management Sciences, Robust Optimization

    For more than a century, election officials across the United States have inspected voting machines before elections using a procedure called Logic and Accuracy Testing (LAT). This procedure consists of election officials casting a test deck of ballots into each voting machine and confirming the machine produces the expected vote total for each candidate. We … Read more

    A robust approach to food aid supply chains

  • Danique de Moor
  • Dick den Hertog
  • H Fleuren
  • Robert Poos
    • Categories Applications - OR and Management Sciences, Robust Optimization Tags , , , ,

    One of the great challenges in reaching zero hunger is to secure the availability of sufficient nourishment in the worst of times such as humanitarian emergencies. Food aid operations during a humanitarian emergency are typically subject to a high level of uncertainty. In this paper, we develop a novel robust optimization model for food aid … Read more