Lan, M. H. (2025) Multi-Objective Evolutionary Optimization for Qujing’s Cultural-Tourism Routes. Journal of Data Analysis ...

The intersection of evolutionary algorithms and data-driven optimisation is reshaping materials science by offering novel computational frameworks for designing and refining materials. Drawing ...

Evolutionary algorithms (EAs) represent a class of heuristic optimisation methods inspired by natural selection and Mendelian genetics. They iteratively evolve a population of candidate solutions ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...

Evolutionary Algorithms are a family of optimisation algorithms inspired by the process of natural selection. They are used to solve complex optimisation problems in various fields, such as ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

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 ...

Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...

The development of vehicle components is a lengthy and therefore very costly process. Researchers have developed a method that can shorten the development phase of the powertrain of battery electric ...

Scientists have developed a smart pulse-shaper integrated on a chip. From the internet, to fibre or satellite communications and medical diagnostics, our everyday life relies on optical technologies.