Those that solve artificially simplified problems where quantum advantage is meaningless. Those that provide no genuine quantum advantage when all costs are properly accounted for. This critique is ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Abstract: The Heterogeneous Fleet Vehicle Routing Problem (HFVRP) aims to find optimal routes for vehicles with different capacities and costs, and is common in real-world applications. Total cost and ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Google DeepMind, Alphabet Inc.’s artificial intelligence research arm, today announced the rollout of Gemini 2.5 Deep Think, a new creative problem-solving AI model. The company stated the model is ...

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Abstract: This study delves into network topology optimization (NTO) as a corrective switching mechanism, designed to effectively manage congestion within power system networks. Our proposed model ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

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