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 ...
Research teams from energy giant ExxonMobil and IBM have been working together to find quantum solutions to one of the most complex problems of our time: managing the tens of thousands of merchant ...
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 ...
A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...
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 ...
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 ...
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 ...
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