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 ...

In order to maximize the efficiency, a heuristic search based algorithm - Genetic Algorithm (GA) is used. The problem is formulated as a multi-objective optimization problem (MOOP) where overall ...

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 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 ...

Quantum optimization team: from left to right are Kilian Ender, Clemens Dlaska, Wolfgang Lechner, Rick van Bijnen, Andreas Kruckenhauser and Glen Bigan Mbeng Quantum computers are often discussed as a ...