Many engineering challenges come down to the same headache—too many knobs to turn and too few chances to test them. Whether tuning a power grid or designing a safer vehicle, each evaluation can be ...

A group of researchers at the Massachusetts Institute of Technology have devised a potentially more effective way of helping computers solve some of the toughest optimization problems they face. Their ...

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 ...

Research teams from energy giant ExxonMobil and IBM have been working together to find quantum solutions to one of the most complex problems of our time: managing the tens of thousands of merchant ...

In the lower part of the figure, it can be seen that L2O leverages on a set of training problem instances from the target optimization problem class to gain knowledge. This knowledge can help identify ...

Optimization seeks to find the best. It could be to design a process that minimizes capital or maximizes material conversion, to choose operating conditions that maximize throughput or minimize waste, ...

An optimization problem is one where you have to make the best decision (choose the best investments, minimize your company’s costs, find the class schedule with the fewest morning classes, or so on).

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 ...