On the Single-Multi-Commodity Gap: Lifting Single- to Multicommodity Flow Instances

Benchmark instances for multicommodity flow problems frequently lack the structural nuances of real-world networks or fail to maintain a rigorous mathematical relationship with their single-commodity counterparts. This paper introduces a formal meta-generation framework that addresses these limitations by lifting single-commodity minimum-cost flow instances into the multicommodity space while strictly preserving the underlying network topology, capacity … Read more

On vehicle routing problems with stochastic demands — Scenario-optimal recourse policies

Two-Stage Vehicle Routing Problems with Stochastic Demands (VRPSDs) form a class of stochastic combinatorial optimization problems where routes are planned in advance, demands are revealed upon vehicle arrival, and recourse actions are triggered whenever capacity is exceeded. Following recent works, we consider VRPSDs where demands are given by an empirical probability distribution of scenarios. Existing … Read more

Time-of-Use Pump Scheduling with Switch Limit and/or Penalty

We study a continuous-time pump scheduling problem for a flow transmission task. A finite table of empirical operating points of pump combinations is given, each point specifying a flow rate and power consumption. Electricity prices follow a time-of-use tariff, and combination changes are penalized or limited by per-shift switch caps. We prove a structural theorem: … Read more

A Newsvendor Model for Last-Mile Fleet Sizing

We study the tactical problem of determining a last-mile delivery fleet size while accounting for day-to-day uncertainty in the number and location of customer requests. An optimally sized fleet must balance the cost of contracting vehicles against the penalty costs of unserved customers: a larger fleet reduces the risk of unserved demand, but a smaller … Read more

Finding Minimal Discretizations in Dynamic Discretization Discovery for Continuous-Time Service Network Design

The dynamic discretization discovery framework is a powerful tool for solving network design problems with a temporal component by iteratively refining a time-discretized model. Existing approaches refine the time discretization in ways that guarantee eventual termination. However, refinement choices are not unique, and better choices can yield smaller and easier-to-solve time-discretized models. We pose the … Read more

Fair Vehicle Routing via Bilevel Optimization

We propose a novel approach to modeling fairness in the Vehicle Routing Problem (VRP) by introducing objective functions based on ordering route lengths, capturing both monotonic and non-monotonic equity measures. Our method ensures allocations that are efficient, capacity-feasible, and equitable according to criteria like min-max, range, Gini, variance, or absolute deviations. To prevent biased or … Read more

Risk-Averse Stochastic User Equilibrium on Uncertain Transportation Networks

Extreme weather events, like flooding, disrupt urban transportation networks by reducing speeds and capacities, and by closing roadways. These hazards create regime-dependent uncertainty in link performance and travel-time distribution tails, challenging conventional traffic assignment that relies on the expectation of cost or mean excess of cost summation. This study develops a risk- and ambiguity-aware traffic … Read more

Approximations for Planar Covering Routes: an Analysis and Application to Public School Transportation

Public school bus routes can change from year to year as students and their home locations change. However, school administrators benefit from the ability to predict future transportation needs on multi-year time scales. With this motivation in mind, this paper develops planning models for school bus routing when student locations are not known with certainty. … Read more