Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

Fuzzy optimisation has emerged as a vital framework for addressing decision-making and extremum problems where data ambiguity and uncertainty preclude the direct application of classical optimisation ...

Scientists have demonstrated a breakthrough application of neutral-atom quantum processors to solve problems of practical use. A collaboration between Harvard University with scientists at QuEra ...

HSBC has begun collaborating with Terra Quantum to investigate using hybrid quantum applications to tackle optimisation challenges. One example of such an issue is collateral optimisation, which is ...

By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...

London, June 5, 2024 – Quantum infrastructure software company Q-CTRL today announced published results that the company says demonstrate a boost of more than 4X in the size of an optimization problem ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

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 ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Microsoft has teamed up with Barclays on a novel approach to tackling artificial intelligence (AI) and optimisation problems based on a scalable analogue optical computer (AOC) architecture, designed ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...