Optimization algorithms and metaheuristics constitute a vital area of computational science, offering robust strategies for tackling complex, multidimensional problems across diverse domains. These ...

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 ...

In the lower part of the figure, it can be seen that L2O leverages on a set of training problem instances from the target optimization problem class to gain knowledge. This knowledge can help identify ...

BOZEMAN, Mont.--(BUSINESS WIRE)--FICO (NYSE: FICO): Global analytics software leader FICO today announced that the 2024 FICO® Xpress Best Paper Award went to a team that developed an algorithm for ...

In large retail operations, category management teams spend significant time deciding which product goes onto which shelf and in which order. Shelf space is very expensive real estate in retail.

Electrical distribution systems are characterized by dynamic operating conditions and complex network topologies, which pose significant challenges for the effective deployment of protection schemes.

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 ...

Many experts believe that once quantum computers are big enough and reliable enough to solve useful problems, the most common deployment architecture will be to have them serve as accelerators for ...

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, ...

Search performance is no longer solely influenced by keywords and backlinks. These days, search engines rely heavily on artificial intelligence to analyse data, ...