Bin packing problems are a class of NP-hard combinatorial optimisation challenges with wide-ranging applications in logistics, manufacturing, cloud computing and scheduling. The fundamental task is to ...

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can ...

Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy predetermined ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

In 1994, a mathematician figured out how to make a quantum computer do something that no ordinary classical computer could. The work revealed that, in principle, a machine based on the rules of ...

In life, we sometimes have to make decisions without all the information we want; that’s true in computer science, too. This is the realm of online algorithms — which, despite their name, don’t ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

AlphaEvolve uses large language models to find new algorithms that outperform the best human-made solutions for data center management, chip design, and more. Google DeepMind has once again used large ...

For a retailer, it’s extremely useful to know whether a customer will be back or has abandoned you for good. Starting in the late 1980s, academic researchers began to develop sophisticated predictive ...