The residential load sector plays a vital role in terms of its impact on overall power balance,
stability, and efficient power management. However, the load dynamics of the energy …

Bilevel optimization is a very active field of applied mathematics. The main reason is that
bilevel optimization problems can serve as a powerful tool for modeling hierarchical …

Bayesian optimization provides sample-efficient global optimization for a broad range of
applications, including automatic machine learning, engineering, physics, and experimental …

Many real-world analytics problems involve two significant challenges: prediction and
optimization. Because of the typically complex nature of each challenge, the standard …

The recent COVID-19 pandemic showed that supply chain resilience is essential for
continuity of many businesses, especially retail chains. However, there are still some …

According to the feed-in tariff for encouraging local consumption of photovoltaic (PV) energy,
the energy sharing among neighboring PV prosumers in the microgrid could be more …

This paper investigates the passive beamforming and information transfer (PBIT) technique
for multiuser multiple-input multiple-output (Mu-MIMO) systems with the aid of reconfigurable …

Questions of 'how best to acquire data'are essential to modelling and prediction in the
natural and social sciences, engineering applications, and beyond. Optimal experimental …

Due to line-of-sight communication links and distributed deployment, Unmanned Aerial
Vehicles (UAVs) have attracted substantial interest in agile Mobile Edge Computing (MEC) …

Stochastic optimization is an umbrella term that includes over a dozen fragmented
communities, using a patchwork of sometimes overlap** notational systems with …