Applications – OR and Management Sciences

Integrated Planning of Drone-Based Disaster Relief: Facility Location, Inventory Prepositioning, and Fleet Operations under Uncertainty

  • Yuyang Ma
  • Karmel S. Shehadeh
  • Man Yiu Tsang
    • Categories Robust Optimization, Transportation

    We introduce a two-stage robust optimization (RO) framework for the integrated planning of a drone-based disaster relief operations problem (DDROP). Given sets of demand points, candidate locations for establishing drone-supported relief facilities, facility types, drone types, and relief items types, our first-stage problem solves the following problems simultaneously: (i) a location problem that determines the … Read more

    Locating Temporary Hospitals and Transporting the Injured Equitably in Disasters

  • Shiva Moslemi
  • Secil Savasaneril
  • Mustafa Tural
    • Categories Applications - OR and Management Sciences, Transportation Tags , , , , , , , ,

    In the aftermath of an earthquake, one of the most critical needs is medical care for the injured. A large number of individuals require immediate attention, often overwhelming the available healthcare resources. The sudden surge in demand, coupled with limited resources, route congestion and infrastructure damage, makes immediate medical care provision a significant challenge. This … Read more

    Data-Driven Optimization for Meal Delivery: A Reinforcement Learning Approach for Order-Courier Assignment and Routing at Meituan

  • Ramon Auad
  • Felipe Lagos
  • Tomas Lagos
    • Categories Dynamic Programming, Meta Heuristics, Transportation Tags

    The rapid growth of online meal delivery has introduced complex logistical challenges, where platforms must dynamically assign orders to couriers while accounting for demand uncertainty, courier autonomy, and service efficiency. Traditional dispatching methods, often focused on short-term cost minimization, fail to capture the long-term implications of assignment decisions on system-wide performance. This paper presents a … Read more

    Extreme Strong Branching for QCQPs

  • Santanu S. Dey
  • Dahye Han
  • Yang Wang
    • Categories (Mixed) Integer Nonlinear Programming, Applications - OR and Management Sciences, Global Optimization

    For mixed-integer programs (MIPs), strong branching is a highly effective variable selection method to reduce the number of nodes in the branch-and-bound algorithm. Extending it to nonlinear problems is conceptually simple but practically limited. Branching on a binary variable fixes the variable to 0 or 1, whereas branching on a continuous variable requires an additional … Read more

    Optimizing pricing strategies through learning the market structure

  • Khosroparviz Naderivarandi
  • Ezgi Karabulut
  • Burak Gokgur
    • Categories Optimization in Data Science, Yield Management Tags , , ,

    This study explores the integration of market structure learning into pricing strategies to maximize revenue in e-commerce and retail environments. We consider the problem of determining the revenue maximizing price of a single product in a market of heterogeneous consumers segmented by their product valuations; and analyze the pricing strategies for varying levels of prior … Read more

    Behaviorally Informed Planning for Retrofitting, Sheltering, and Mixed-Mode Evacuation in Urban Tsunami Preparedness: Toward a Tsunami-Resilient Istanbul

  • Shiva Moslemi
  • Vedat Bayram
  • Baris Yildiz
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Transportation Tags , , , , ,

    Tsunamis, primarily triggered by earthquakes, pose critical threats to coastal populations due to their rapid onset and limited evacuation time. Two main protective actions exist: sheltering in place, which requires substantial retrofitting investments, and evacuation, which is often hindered by congestion, mixed travel modes, and tight inundation times. Given pedestrians’ slower movement and restricted evacuation … Read more

    Political districting to maximize whole counties

  • Maral Shahmizad
  • Austin Buchanan
    • Categories Applications - OR and Management Sciences, Combinatorial Optimization, Integer Programming Tags , , ,

    We consider a fundamental question in political districting: How many counties can be kept whole (i.e., not split across multiple districts), while satisfying basic criteria like contiguity and population balance? To answer this question, we propose integer programming techniques based on combinatorial Benders decomposition. The main problem decides which counties to keep whole, and the … Read more

    Optimizing Expeditionary Logistics: Dynamic Discretization for Fleet Management

  • Haden Boone
  • Mathieu Dahan
    • Categories (Mixed) Integer Linear Programming, Network Optimization, Production and Logistics Tags , , ,

    We introduce the Expeditionary Logistics Network Design Problem (ELNDP), a new formulation for operational-level planning in expeditionary environments where multi-modal vehicle coordination is critical and penalties for unmet demand dominate transportation costs. ELNDP extends the classical Scheduled Service Network Design Problem by incorporating flexible commodity sourcing and heterogeneous vehicle capabilities, both essential in military logistics. … Read more

    Consolidation in Crowdshipping with Scheduled Transfer Lines: A Surrogate-Based Network Design Framework

  • Ramazan Çevik
  • Ali Şardağ
  • Barış Yıldız
    • Categories Combinatorial Optimization, Optimization in Data Science, Transportation Tags , , ,

    Abstract: Crowdshipping has gained attention as an emerging delivery model thanks to advantages such as flexibility and an asset-light structure. Yet, it chronically suffers from a lackof mechanisms to create and exploit consolidation opportunities, limiting its efficiency and scalability. This work contributes to the literature in two ways: first, by introducing a novel consolidation concept … Read more

    On vehicle routing problems with stochastic demands — Generic integer L-shaped formulations

  • Matheus Jun Ota
  • Ricardo Fukasawa
    • Categories Branch and Cut Algorithms, Stochastic Programming, Transportation Tags , , ,

    We study a broad class of vehicle routing problems in which the cost of a route is allowed to be any nonnegative rational value computable in polynomial time in the input size. To address this class, we introduce a unifying framework that generalizes existing integer L-shaped (ILS) formulations developed for vehicle routing problems with stochastic … Read more