Quantum computers of the future hold promise for solving complex problems more quickly than ordinary computers. For example, they can factor large numbers exponentially faster than classical ...

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...

We describe a genetic algorithm (GA) for designing efficient search paths, against a moving target, in complicated environments. The immediate application is acoustic search for submarines, but the ...

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 ...

We present a genetic algorithm for the multiple-choice integer program that finds an optimal solution with probability one (though it is typically used as a heuristic). General constraints are relaxed ...

Quantum approximate optimization algorithm can be implemented using Rydberg atoms 14 Apr 2022 Quantum optimization team: from left to right are Kilian Ender, Clemens Dlaska, Wolfgang Lechner, Rick van ...