Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

Over the last decade, the field of nanophotonics (or nano-optics) has been developing rapidly, mainly driven by plasmonics, because noble metal nanoparticles allow plasmon resonances to be spectrally ...

This research explores how user-defined constraints affect the efficiency and effectiveness of multi-objective evolutionary algorithm (MOEA) optimization in water resources. Constraints in MOEA ...

The urban low-altitude logistics network adopts a hub-and-spoke, multi-layered structure. Its nodes are waypoints mapped to corresponding altitude layers based on spoke nodes (delivery spots) and hub ...

Resident data scientist Dr. James McCaffrey of Microsoft Research turns his attention to evolutionary optimization, using a full code download, screenshots and graphics to explain this machine ...

Evolutionary optimization is a technique that can be used to train many types of machine learning models. Evolutionary optimization loosely models the biological processes of natural selection, ...