Global optimisation methods and algorithms are pivotal in addressing complex problems where the objective function is often non‐convex, multi‐modal, or even presented as a black‐box with expensive ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

An important aspect in software engineering is the ability to distinguish between premature, unnecessary, and necessary ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

The power generation sector has been challenged by trends in digitalization, growth of intermittent renewables, equipment performance improvements, new generation, and storage technologies.

Electromagnetic (EM) wave front modulation has important significance in both scientific researches and industrial applications. However, conventional dielectric materials have limited choices of ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

Computer-aided simulation and optimisation methods offer comprehensive possibilities for analysing and improving thermoelectric generators (TEG). Our technical expertise and access to extensive ...