Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

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 ...

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 ...

An international team led by the Clínic-IDIBAPS-UB along with the Institute of Cancer Research, London, has developed a new method based on DNA methylation to decipher the origin and evolution of ...

Research published in Nature Ecology & Evolution introduces a novel method for inferring DNA methylation patterns in non-skeletal tissues from ancient specimens, providing new insights into human ...

Security researchers have unveiled a new optimization algorithm that borrows its logic from the human immune system, and it ...

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 ...

Optimization problems rarely have a single right answer. In engineering design, scheduling, and machine learning, decision ...

Imagine a very complex problem—supply chain optimization, for example—in which a computer generates millions of trial solutions completely at random and then ...

The changing use of the word algorithm reflects this enhanced visibility. In fact, the meaning of this word has changed ...