Comparison of Genetic Algorithm and Quantum Genetic Algorithm

Evolving solutions rather than computing them certainly represents a promising programming approach. Evolutionary computation has already been known in computer science since more than 4 decades. More recently, another alternative of evolutionary algorithms was invented: quantum genetic algorithms (QGA). In this paper, we outline the approach of QGA by giving a comparison with conventional genetic algorithm (CGA). Our results have shown that QGA can be a very promising tool for exploring search spaces.