Quantum-Enhanced Selection Operators for Evolutionary Algorithms. (arXiv:2206.10743v1 [quant-ph])

Genetic algorithms have unique properties which are useful when applied to
black box optimization. Using selection, crossover, and mutation operators,
candidate solutions may be obtained without the need to calculate a gradient.
In this work, we study results obtained from using quantum-enhanced operators
within the selection mechanism of a genetic algorithm. Our approach frames the
selection process as a minimization of a binary quadratic model with which we
encode fitness and distance between members of a population, and we leverage …

algorithms arxiv evolutionary algorithms operators quantum