Distributionally Robust Fair Transit Resource Allocation During a Pandemic

This paper studies Distributionally robust Fair transit Resource Allocation model (DrFRAM) under Wasserstein ambiguity set to optimize the public transit resource allocation during a pandemic. We show that the proposed DrFRAM is highly nonconvex and nonlinear and is, in general, NP-hard. Fortunately, we show that DrFRAM can be reformulated as a mixed-integer linear programming (MILP) … Read more

Robust Epidemiological Prediction and Optimization

The COVID-19 pandemic has brought many countries to their knees, and the urgency to return to normalcy has never been greater. Epidemiological models, such as the SEIR compartmental model, are indispensable tools for, among other things, predicting how pandemic may spread over time and how vaccinations and different public health interventions could affect the outcome. … Read more

On the Formulation Dependence of Convex Hull Pricing

Convex hull pricing provides a potential solution for reducing out-of-market payments in wholesale electricity markets. This paper revisits the theoretical construct of convex hull pricing and explores its important but underappreciated formulation-dependence property. Namely, convex hull prices may change for different formulations of the same unit commitment problem. After a conceptual exposition of the property, … Read more

Long-Run Optimal Pricing in Electricity Markets with Non-Convex Costs

Determining optimal prices in non-convex markets remains an unsolved challenge. Non-convex costs are critical in electricity markets, as startup costs and minimum operating levels yield a non-convex optimal value function over demand levels. While past research largely focuses on the performance of different non-convex pricing frameworks in the short-run, we determine long-run adapted resource mixes … Read more

Optimal Eco-Routing for Hybrid Vehicles with Mechanistic/Data-Driven Powertrain Model Embedded

Hybrid Electric Vehicles (HEVs) are regarded as an important (transition) element of sustainable transportation. Exploiting the full potential of HEVs requires (i) a suitable route selection and (ii) suitable power management, i.e., deciding on the split between combustion engine and electric motor usage as well as the mode of the electric motor, i.e., driving or … Read more

Dynamic Repositioning in Free-Floating Bike Sharing Systems Using Approximate Dynamic Programming

In bike sharing systems, the spatiotemporal imbalance of bike flows leads to shortages of bikes in some areas and overages in some others, depending on the time of the day, resulting in user dissatisfaction. Repositioning needs to be performed timely to deal with the spatiotemporal imbalance and to meet customer demand in time. In this … Read more

Nonconvex Equilibrium Models for Energy Markets: Exploiting Price Information to Determine the Existence of an Equilibrium

Motivated by examples from the energy sector, we consider market equilibrium problems (MEPs) involving players with nonconvex strategy spaces or objective functions, where the latter are assumed to be linear in market prices. We propose an algorithm that determines if an equilibrium of such an MEP exists and that computes an equilibrium in case of … Read more

High quality timetables for Italian schools

This work introduces a complex variant of the timetabling problem, which is motivated by the case of Italian schools. The new requirements enforce to (i) provide the same idle times for teachers, (ii) avoid consecutive \emph{heavy} days, (iii) limit daily multiple lessons for the same class, (iv) introduce shorter time units to differentiate entry and … Read more

‘Pro-poor’ humanitarian logistics: Prioritizing the vulnerable in allocating relief aid

This paper builds on the premise that the most vulnerable areas or groups of people should be protected from disasters by being given priority in humanitarian operations, particularly when there are limited resources available for disaster management. The basis and the development of the paper are strongly aligned with the United Nations’ Sustainable Development Goals … Read more

MIMO Radar Optimization With Constant-Modulus and Any p-Norm Similarity Constraints

MIMO radar plays a key role in autonomous driving, and the similarity waveform constraint is an important constraint for radar waveform design. However, the joint constant-modulus and similarity constraint is a difficult constraint. Only the special case with $\infty$-norm similarity and constant-modulus constraints is tackled by the semidefinite relaxation (SDR) and the successive quadratic refinement … Read more