Global optimisation stands as a pivotal discipline in applied mathematics and engineering, providing robust methodologies for determining the absolute best solution among myriad local optima. Recent ...

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 ...

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.

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 ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Modern optimization theory, algorithms, and applications in process engineering. Topics include the fundamentals of linear programming, integer programming, nonlinear programming, mixed-integer ...

A research team has developed DeepCodon, a deep learning–based codon optimization tool that significantly improves heterologous protein expression in Escherichia coli while preserving functionally ...