Prior efforts to develop hardware for optimization problems have involved Ising machines, a category of hardware solvers that incorporate the Ising model to find the absolute or approximate “ground ...

We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

The researchers say that the innovations in math and algorithms they have developed are as critical as the machine itself in solving optimization problems. The novel type of algorithm being used in ...

Until now, hardware architectures for Ising machines could efficiently solve problems with quadratic polynomial objective functions but were not scalable to increasingly relevant higher-order ...

Cambridge Quantum reveals new algorithm for solving combinatorial optimization problems with business use-cases.

“When solving a very large computational problem, optimization solvers can require significant computational time to find a first feasible solution,” said Dr. Timo Berthold, director of Mixed ...

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

Advanced AI-based techniques scale-up solving complex combinatorial optimization problems Date: June 10, 2024 Source: University of California - San Diego Summary: A framework based on advanced AI ...

It’s widely known that quantum computers are well suited for solving optimization problems, an application which is a front-runner for showing performance improvements over classical computation ...