Quantum-inspired evolutionary algorithms, one of the three main research areas related to
the complex interaction between quantum computing and evolutionary algorithms, are …

This paper introduces a new evolutionary algorithm with the support of an actual quantum
processor, a computing device which uses phenomena from quantum mechanics to enable …

From recent research on combinatorial optimization of the knapsack problem, quantum-
inspired evolutionary algorithm (QEA) was proved to be better than conventional genetic …

Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian
natural selection. They are popular heuristic optimisation methods based on simulated …

Obtaining efficient optimisation algorithms has become the focus of much research interest
since current developing trends in machine learning, traffic management, and other cutting …

This paper presents a review of quantum-inspired population-based metaheuristics.
Quantum-inspired algorithms were born when there were no quantum computers; they …

Since they were proposed as an optimization method, evolutionary algorithms (EA) have
been used to solve problems in several research fields. This success is due, besides other …

This paper proposes a novel evolutionary algorithm inspired by quantum computing, called
a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and …

The complexity of the selection procedure of a genetic algorithm that requires reordering, if
we restrict the class of the possible fitness functions to varying fitness functions, is, where is …

The quantum-inspired evolutionary algorithm (QEA) applies several quantum computing
principles to solve optimization problems. In QEA, a population of probabilistic models of …