High penetrations of variable renewable energy introduce significant resource adequacy challenges, particularly when weather-driven uncertainty affects renew...

Managing electric bus (EB) fleets at scale introduces operational challenges that differ fundamentally from those of conventional fuel-powered fleets. A main...

This work introduces ADS-PB, an extension of the Adaptive Direct Search (ADS) framework for solving constrained blackbox optimization problems. With ADS, it...

Heavy-duty vehicles (HDVs) are a major source of road transportation emissions, yet their electrification remains challenging due to operational constraints....

Hydropower generation fulfills 94% of Québec’s electricity needs, making efficient Short-Term Hydropower Scheduling (STHS) critical for daily operations. Thi...

This work surveys the different parallel variants of the mesh adaptive direct search (MADS) algorithm for constrained blackbox optimization. These problems c...

Lithium-ion batteries (LIBs) are currently the core energy storage component of electric vehicles (EVs). Real-time, accurate, and robust state-of-charge (SO...

Accurate estimation of metal accumulation in electric arc furnaces (EAFs) is critical for maintaining stable ferrosilicon (FeSi) production and ensuring effe...

Task offloading in edge computing becomes significantly more challenging when applications are modeled as Directed Acyclic Graphs (DAGs), where task dependen...

To meet the increasing demand for low-latency processing in mobile and IoT devices, edge computing offloads user application tasks to nearby cloudlets (edge ...

We investigate a state estimation problem for a linear time-invariant Gaussian system, based on a measured scalar privacy-sensitive signal. This is formulate...

Large Language Models (LLMs) are increasingly used as proxies for human respondents in social science, behavioral, and marketing experiments, yet their synth...

We study the solution of symmetric positive-definite linear systems by way of families of full- and limited-memory methods. Our contributions are threefol...

The almost supermartingale convergence theorem of Robbins and Siegmund (1971) is a fundamental tool for establishing the convergence of various stochastic it...

Optical transport networks (OTNs) carry Ethernet traffic over lightpaths that can be provisioned using elastic optical networks (EONs) with flexible spectrum...

We consider the penalized security-constrained optimal power flow (SCOPF) problem in a linearized form where thermal line limits are enforced as soft constr...

This paper investigates mean field games and control on sparse networks. In the case of large expander graphs, the limit topologies are analyzed using the gr...

The design of tactical wireless networks reflects a complex interplay among structural constraints, technological choices, and underlying modeling assumption...

Tactical wireless networks play a vital role in ensuring reliable connectivity in scenarios where conventional telecommunications infrastructure is unavailab...

Bilevel optimization involves an upper-level and a lower-level decision maker. The lower-level optimization problem is nested within the constraints of the ...