Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...
It remains an open question when a commercial quantum computer will emerge that can outperform classical (non-quantum) ...
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 ...
MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.
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 ...
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 ...
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Fully digital design paves the way for scalable probabilistic computing
Artificial intelligence and machine learning could become dramatically more efficient, thanks to a new type of computer ...
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 ...
The Amplify SDK enables simple, efficient development and unified handling of quantum and optimization solvers [1]. The Amplify AE is a large-scale Ising machine that solves combinatorial optimization ...
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 ...
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