Abstract Evolving solutions rather than computing them certa inly 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 Convent ional Genetic Algorithm (CGA). Our results have shown that QGA can be a very promising tool for exploring search space s.

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