The cosine measure was introduced in 2003 to quantify the richness of a finite positive spanning sets of directions in the context of derivative-free direc...

Inventory management for slow-moving items is challenging due to their high intermittence and lumpiness. Recent developments in machine learning and computat...

This paper introduces the Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions (HEVRP-NL). This problem involves routing a ...

A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...

In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...

Determining optimal inventory replenishment decisions requires balancing the costs of excess inventory with shortage risks. While demand uncertainty has been...

In this work, we propose a non-intrusive and training free method to detect behind-the-meter (BTM) electric vehicle (EV) charging events from the data measur...

The Harwell Subroutine Library (HSL) is a renowned suite of efficient and robust numerical algorithms designed to tackle complex mathematical problems such a...

We show that the two-stage minimum description length (MDL) criterion widely used to estimate linear change-point (CP) models corresponds to the marginal lik...

We study the relation between the promotion of a cryptocurrency on Twitter and its return dynamics around pump-and-dump events. By analyzing abnormal retur...

Monte Carlo (MC) is widely used for the simulation of discrete time Markov chains. We consider the case of a \(d\)-dimensional continuous state space and w...

Randomized Quasi-Monte Carlo (RQMC) methods provide unbiased estimators whose variance often converges at a faster rate than standard Monte Carlo as a functi...

This work introduces a novel multi-fidelity blackbox optimization algorithm designed to alleviate the resource-intensive task of evaluating infeasible points...

This study addresses large-scale personnel scheduling problems in the service industry by combining mathematical programming with data mining techniques to...

We consider the set of graphs that can be constructed from a one-vertex graph by repeatedly adding a clique or a stable set linked to all or none of the vert...

Incentive-based demand response aggregators are widely recognized as a powerful strategy to increase the flexibility of residential community microgrid (RCM)...

In this paper, a mixed integer nonlinear model for the short-term hydropower optimization problem considering operational constraints such as demand and st...

Classical mean field games (MFG) have been concerned with large games amongst symmetrically influential agents with asymptotically negligible weight. In th...

Reinforcement learning (RL) for partially observable Markov decision processes (POMDPs) is a challenging problem because decisions need to be made based on t...

We review the development of the concept of effective bandwidth from its origin in the planning and management of ATM networks. We start with the extension...