Abstract: Genetic programming approaches have previously been employed in the literature to evolve heuristics for various combinatorial optimisation problems. This paper presents a hyper-heuristic ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

From analog hobbies to tech curfews, these Gen Zers are experimenting with science-backed ways to help their brains feel a little less foggy. Doomscrolling has taken over our screen time, and ...

It can be used in any kind of .NET 6, .NET Standard, and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin ...

The manufacturing sector grapples with persistent challenges marked by inefficiencies, production errors, and the burden of costly machine maintenance. These issues, rooted in manual processes, human ...

Finding bipartite matchings is one of the oldest and most well-studied problems in computer science. This problem comes up in many guises, such as when matching donors to recipients for organ ...

Industrial and economic development primarily occurs in densely populated urban areas in Taiwan. The outbreak of war in such areas could have severe consequences. Disaster relief and homeland defense ...

Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...

Two-dimensional (2D) irregular packing problems are widespread in manufacturing industries such as shipbuilding, metalworking, automotive production, aerospace, clothing and furniture manufacturing.