When vehicles cross the 100,000-mile threshold, drivers often confront a cascade of expensive repairs that strain household ...

A team of researchers at the University of Waterloo have made a breakthrough in quantum computing that elegantly bypasses the ...

Approaching conversion earlier changes how teams work. Instead of reacting to poor results, they focus on clarity, alignment, ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Abstract: Plenty of decision variable grouping-based algorithms have shown satisfactory performance in solving high-dimensional optimization problems. However, most of them are tailored for ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

If you want to accentuate the importance of a problem, it seems sensible to explain how prevalent it is. Lots of people are at risk of Alzheimer’s disease. Lots of women carry a gene that makes them ...

1 School of Mathematics and Statistics, Fuzhou University, Fuzhou, China. 2 College of Computer and Data Science, Fuzhou University, Fuzhou, China. In this paper, we use Physics-Informed Neural ...

The paper presents a topology optimization methodology for 2D elastodynamic problems using the boundary element method (BEM). The topological derivative is derived based on the variation method and ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Abstract: Ising machines are next-generation computers expected to efficiently sample near-optimal solutions of combinatorial optimization problems. Combinatorial optimization problems are modeled as ...