Applications – OR and Management Sciences

Forecasting Urban Traffic States with Sparse Data Using Hankel Temporal Matrix Factorization

  • Chun Cheng
    • Categories Data Science Algorithms, Data Science Applications, Transportation Tags , , , ,

    Forecasting urban traffic states is crucial to transportation network monitoring and management, playing an important role in the decision-making process. Despite the substantial progress that has been made in developing accurate, efficient, and reliable algorithms for traffic forecasting, most existing approaches fail to handle sparsity, high-dimensionality, and nonstationarity in traffic time series and seldom consider … Read more

    Equity-Driven Workload Allocation for Crowdsourced Last-Mile Delivery

  • Abhay Sobhanan
  • Hadi Charkhgard
  • Iman Dayarian
    • Categories Meta Heuristics, Multi-Criteria Optimization, Transportation Tags , , , ,

    Crowdshipping, a rapidly growing approach in Last-Mile Delivery (LMD), relies on independent crowdworkers for delivery orders. Building a sustainable network of crowdshippers is essential for the survival and growth of such systems, while their participation is primarily motivated by fair pay. Additionally, the financial well-being of crowdworkers is sensitive to fair compensation, especially for those … Read more

    Cluster branching for vehicle routing problems

  • Joao Marcos P Silva
  • Eduardo Uchoa
  • Anand Subramanian
    • Categories Applications - OR and Management Sciences, Combinatorial Optimization, Integer Programming Tags , , ,

    This article introduces Cluster Branching, a novel branching strategy for exact algorithms solving Vehicle Routing Problems (VRPs). While branching is crucial for the efficiency of branch-and-bound-based algorithms, existing branching types such as Edge Branching, CutSet Branching, and Ryan&Foster Branching have their limitations. The proposed branching strategy aggregates multiple edge variables into higher-level decision structures corresponding … 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 problem of assigning the entries of a household data set to real-world address data. This household assignment problem occurs in the geo-referencing step of spatial microsimulation models. The resulting combinatorial optimization model is a maximum weight matching problem with additional side constraints. Even for real-world instances of medium size, such as the … Read more

    Routing a fleet of unmanned aerial vehicles: a trajectory optimisation-based framework

  • Walton P. Coutinho
  • Jörg Fliege
  • Maria Battarra
  • Anand Subramanian
    • Categories (Mixed) Integer Nonlinear Programming, Applications - OR and Management Sciences, Systems governed by Differential Equations Optimization Tags , ,

    We consider an aerial survey operation in which a fleet of unmanned aerial vehicles (UAVs) is required to visit several locations and then land in one of the available landing sites while optimising some performance criteria, subject to operational constraints and flight dynamics. We aim to minimise the maximum flight time of the UAVs. To … Read more

    Toll Setting with Robust Wardrop Equilibrium Conditions Under Budgeted Uncertainty

  • Yasmine Beck
  • Martine Labbé
  • Martin Schmidt
    • Categories (Mixed) Integer Nonlinear Programming, Robust Optimization, Transportation Tags , , , ,

    We consider two variants of the toll-setting problem in which a traffic authority uses tolls either to maximize revenue or to alleviate bottlenecks in the traffic network. The users of the network are assumed to act according to Wardrop’s user equilibrium so that the overall toll-setting problems are modeled as mathematical problems with equilibrium constraints. … Read more

    Incorporating Service Reliability in Multi-depot Vehicle Scheduling: A Chance-Constrained Approach

  • Margarita P Castro
  • Merve Bodur
  • Amer Shalaby
    • Categories Cutting Plane Approaches, Stochastic Programming, Transportation Tags , , ,

    The multi-depot vehicle scheduling problem (MDVSP) is a critical planning challenge for transit agencies. We introduce a novel approach to MDVSP by incorporating service reliability through chance-constrained programming (CCP), targeting the pivotal issue of travel time uncertainty and its impact on transit service quality. Our model guarantees service reliability measured by on-time performance (OTP), a … Read more

    Robustness Analysis for Adaptive Optimization With Application to Industrial Decarbonization in the Netherlands

  • Justin Starreveld
  • Dick den Hertog
  • Jaron Davelaar
  • gregorbrandt
  • Nort Thijssen
    • Categories Applications - OR and Management Sciences, Energy, Robust Optimization Tags , , ,

    Robustness analysis assesses the performance of a particular solution under variation in the input data. This is distinct from sensitivity analysis, which assesses how variation in the input data changes a model’s optimal solution. For risk assessment purposes, robustness analysis has more practical value than sensitivity analysis. This is because sensitivity analysis, when applied to … Read more

    Efficient Project Scheduling with Autonomous Learning Opportunities

  • Alessandro Hill
  • Thomas Vossen
    • Categories Combinatorial Optimization, Scheduling

    We consider novel project scheduling problems in which the experience gained from completing selected activities can be used to accelerate subsequent activities. Given a set of potential learning opportunities, our model aims to identify the opportunities that result in a maximum reduction of the project makespan when scheduled in sequence. Accounting for the impact of … Read more

    Counterfactual Explanations for Linear Optimization

  • Jannis Kurtz
  • Ş. İlker Birbil
  • Dick den Hertog
    • Categories Applications - OR and Management Sciences, Linear Programming Tags , , ,

    The concept of counterfactual explanations (CE) has emerged as one of the important concepts to understand the inner workings of complex AI systems. In this paper, we translate the idea of CEs to linear optimization and propose, motivate, and analyze three different types of CEs: strong, weak, and relative. While deriving strong and weak CEs … Read more