Distributionally Robust Disaster Relief Planning under the Wasserstein Set

We study a two-stage natural disaster management problem modeled as a stochastic program, where the first stage consists of a facility location problem, deciding where to open facilities and pre-allocate resources such as medical and food kits, and the second stage is a fixed-charge transportation problem, routing resources to affected areas after observing a disaster. … Read more

Courier satisfaction in rapid delivery systems using dynamic operating regions

Rapid delivery systems where an order is delivered to a customer from a local distribution point within minutes or hours have experienced rapid growth recently and often rely on gig economy couriers. The prime example is a meal delivery system. During an operating day, couriers in such a system are used to deliver orders placed … Read more

Optimizing investment allocation: a combination of Logistic Regression and Markowitz model

One of the biggest challenges in quantitative finance is the efficient allocation of capital. Thus, in this study, a two-step methodology was proposed, in which a combination of logistic regression and Markowitz model was performed to determine optimized portfolios. In this context, in the first step, fundamentalist indicators were used as inputs to the logistic … Read more

Operation of an ambulance fleet under uncertainty

We introduce two new optimization models for the dispatch of ambulances. These models are to our knowledge the first providing a full modelling of the operation of an ambulance fleet, taking into account all or almost all constraints of the problem. The first model, called the ambulance selection problem, is used when an emergency call … Read more

Modeling uncertainty processes for multi-stage optimization of strategic energy planning: An auto-regressive and Markov chain formulation

This paper deals with the modeling of stochastic processes in long-term multistage energy planning problems when little information is available on the degree of uncertainty of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through autoregressive (AR) … Read more

Intraday Power Trading: Towards an Arms Race in Weather Forecasting?

We propose the first weather-based algorithmic trading strategy on a continuous intraday power market. The strategy uses neither production assets nor power demand and generates profits purely based on superior information about aggregate output of weather-dependent renewable production. We use an optimized parametric policy based on state-of-the-art intraday updates of renewable production forecasts and evaluate … Read more

Exact Solutions to a Carsharing Pricing and Relocation Problem under Uncertainty

In this article we study the problem of jointly deciding carsharing prices and vehicle relocations. We consider carsharing services operating in the context of multi-modal urban transportation systems. Pricing decisions take into account the availability of alternative transport modes, and customer preferences with respect to these. In order to account for the inherent uncertainty in … Read more

An efficient solution methodology for the airport slot allocation problem with preprocessing and column generation

Airport coordination is a demand control mechanism that maximizes the use of existing infrastructure at congested airports. Aircraft operators submit a list of regular flights that they wish to operate over a five to seven-month period and a designated coordinator is responsible for allocating the available airport slots, which represent the permission to operate a … Read more

Randomized Policy Optimization for Optimal Stopping

Optimal stopping is the problem of determining when to stop a stochastic system in order to maximize reward, which is of practical importance in domains such as finance, operations management and healthcare. Existing methods for high-dimensional optimal stopping that are popular in practice produce deterministic linear policies — policies that deterministically stop based on the … Read more

Efficient Formulations for Multiple Allocation Hub Network Interdiction Problems

In this paper, we study a network interdiction problem on a multiple allocation, uncapacitated hub network. The problem is formulated as a bilevel Stackelberg game between an attacker and a defender, where the attacker identifies r out of p hubs to interdict so as to maximize the worst-case post-interdiction performance of the system with the … Read more