Combinatorial optimisation addresses the search for optimal configurations within discrete, often high‐dimensional spaces, where the number of feasible solutions grows exponentially with problem size.

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Memristor-based chips could solve demanding optimization problems far faster and with less energy by replacing dense ...

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 ...

Researchers at the University of Gothenburg have developed a novel Ising machine that utilizes surface acoustic waves as an effective carrier of dense information flow. This approach enables fast, ...

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 ...

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 ...

This type of problem – known as a combinatorial optimization problem – lies at the heart of many challenges in science, technology, and business. A new German-Taiwanese research project involving TU ...

The proposed algorithm combines variational scheduling with post-processing to achieve near-optimal solutions to combinatorial optimization problems with constraints within the operation time of ...

Combinatorial optimization problems are encountered often in various real-world applications, including logistics, scheduling, and network design ...

Dr. James McCaffrey of Microsoft Research shows how to implement simulated annealing for the Traveling Salesman Problem (find the best ordering of a set of discrete items). The goal of a combinatorial ...