New AutoRL methods using hyperparameter optimization and metalearning achieve best solutions in 23 of 28 Sequential Ordering ...

Newswise — 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 study ...

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, ...

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 ...

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 ...

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 ...

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.

An enhanced particle swarm optimization algorithm improves mixed electric and fuel vehicle routing solutions by an average of ...

In a new development that is most likely to establish a new industry standard, scientists at Cambridge Quantum (CQ) have created a new algorithm for solving combinatorial optimization problems that ...

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 ...