DYNA JOURNAL ENGINEERING

Key words:

QGA, IQGA, GA, genetic algorithm, Quantum Genetic Algorithm, quantum computing, quantum optimization, hybrid algorithms, evolutionary computation, quantum parallelism, qubits, superposition, algorithmic complexity, machine learning integration, quantum-inspired computation, algoritmo genético, algoritmo genético cuántico, computación cuántica

Article type:

ARTICULO DE INVESTIGACION / RESEARCH ARTICLE

Section:

RESEARCH ARTICLES

This survey presents a comprehensive analysis of the Improved Quantum Genetic Algorithm (IQGA), an interesting way of applying quantum computing to genetic algorithms (GAs). The study begins with an introduction to the several variants of Quantum Genetic Algorithm (QGA), which are widely used in different applications of GAs. The article introduces the IQGA as a quantum version of the classical GA, detailing how it leverages quantum parallelism and superposition to reduce the time complexity of the genetic operations, and highlighting its crucial role in quantum algorithms. The analysis also addresses the mathematical foundations of the IQGA, and the key advantages and challenges associated with its use in several applications. Finally, it concludes with an exploration of the current and potential applications of IQGA and common characteristics of several implementations of IQGAs.

Keywords: QGA, IQGA, GA.