Evolutionary optimization algorithms constitute a class of derivative-free techniques inspired by principles of natural selection and genetics, tailored to optimise continuous real-valued functions.

In a new UCLA-led study, investigators shed light on the intricate processes underlying cancer evolution and define the optimal algorithms to analyze the genetic makeup of tumors. Understanding the ...

A team led by Prof Frank Glorius from the Institute of Organic Chemistry at the University of Münster has developed an evolutionary algorithm that identifies the structures in a molecule that are ...

Evolutionary algorithms are population-based optimisation techniques inspired by natural selection and genetic variation. Traditionally driven by pseudo-random number generators, these methods ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more A new technique developed by much-hyped ...

A team of researchers led by Yumin Dong of Chongqing Normal University has developed a novel method to optimize parametric quantum circuits, a critical component of variational quantum algorithms. The ...

Evolution is a very slow process, due largely to the fact that nature doesn't "know" in advance which features of an animal will be beneficial. A new AI-based algorithm does know, however, allowing it ...