Abstract Energy Systems Modelling is growing in relevance on providing insights and
strategies to plan a carbon-neutral future. The implementation of an effective energy …

This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

Many optimal decision problems in scientific, engineering, and public sector applications
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …

A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP)
problems using standard formulation techniques. However, in some cases the resulting MIP …

Large-scale renewable energy integration decreases the system inertia and restricts
frequency regulation. To maintain the frequency stability, allocating adequate frequency-sup …

Tropical geometry is a relatively recent field in mathematics and computer science,
combining elements of algebraic geometry and polyhedral geometry. The scalar arithmetic …

Estimating punching shear capacity is an important task in the design of steel fibre
reinforced concrete (SFRC) flat slabs. The accuracy of commonly employed empirical …

In data mining, regression analysis is a computational tool that predicts continuous output
variables from a number of independent input variables, by approximating their complex …

Battery energy storage (BES) systems play an increasingly important part in power system
operation because of their high efficiency and decreasing cost. This article proposes a …

With the democratization of cloud and datacenter computing, users increasingly share large
hardware platforms. In this setting, architects encounter two challenges: sharing fairly and …