Quantum-inspired swarm optimisation applies principles of quantum mechanics to enhance swarm intelligence algorithms for complex systems. It extends classical particle swarm optimisation by ...

Researchers have developed a quantum particle swarm optimization algorithm for maximum power point tracking that reportedly generates 3.33% more power in higher temperature tests and 0.89% more power ...

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 ...

Quantum-inspired optimisation algorithms represent a class of metaheuristic techniques that draw inspiration from quantum mechanics to tackle combinatorial optimisation problems on classical hardware.

Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...

Researchers have suggested to use a hybrid version of the so-called salp swarm algorithm (SSA) algorithm for maximum power point tracking in PV systems operating under highly fluctuating environmental ...

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 ...

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 ...