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.

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 ...

Combinatorial optimisation techniques play a central role in designing networks that require discrete decision-making under constraints. At its core, a network design problem seeks the optimal ...

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 ...

Traffic congestion has been worsening since the 1950s in large cities thanks to the exorbitant number of cars sold each year. Unfortunately, the figurative price tag attached to excessive traffic ...

Scientists at Tokyo Institute of Technology have designed a novel processor architecture that can solve combinatorial optimization problems much faster than existing ones. Combinatorial optimization ...

Scientists have designed a novel processor architecture that can solve combinatorial optimization problems much faster than existing ones. Combinatorial optimization are complex problems that show up ...

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 ...

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 ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

Hardware technology has been developed that can solve the core challenge of the big data and artificial intelligence era—the "combinatorial optimization problem"—faster and more efficiently. A ...