Combinatorial optimisation problems arise in many fields, from logistics and network design to machine learning and bioinformatics. Most classical formulations are NP-hard, rendering exact ...

Combinatorial optimization addresses decision problems on discrete structures, such as routing, scheduling and network design, whose exact solution often lies beyond feasible computational limits.

The traveling salesman problem is considered a prime example of a combinatorial optimization problem. Now a Berlin team led by theoretical physicist Prof. Dr. Jens Eisert of Freie Universität Berlin ...

In the era of big data and artificial intelligence, a new approach has emerged for solving combinatorial optimization problems, which involves finding the most efficient solution among many possible ...

Bicycle sharing systems have become an attractive option to alleviate traffic in congested cities. However, rebalancing the number of bikes at each port as time passes is essential, and finding the ...

In this graduate-level course, we will be covering advanced topics in combinatorial optimization. We will start with matchings and cover many results, extending the fundamental results of matchings, ...

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 ...

A new technical paper titled “Analog optical computer for AI inference and combinatorial optimization” was published by researchers at Microsoft Research, Barclays and University of Cambridge.

Although computers are overwhelmingly digital today, there’s a good point to be made that analog computers are the more efficient approach for specific applications. The authors behind a recent paper ...

Entanglement, Inc., a next-generation computing and AI company advancing quantum logic, optimization, and artificial intelligence, today announced that its Chief Research Scientist, Dr. Fred Glover, ...