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 ...
The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...
From planning transportation networks to organizing massive datasets, many of society's most important challenges boil down to an optimization problem: finding the best solution among an enormous ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results