Among the various stochastic optimization methods, population-based algorithms inspired by nature are widely acclaimed and preferred. These approaches replicate problem-solving strategies employed by ...

The Crayfish Optimization Algorithm (COA) is a recent powerful algorithm that is sometimes plagued by poor convergence speed and a tendency to rapidly converge to the local optimum. This study ...

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 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 ...