Arman Process Journal (APJ)
Quarterly Journal of Information and Communication Technology ​

Investigating the Quantum Genetic Algorithms in the Field of Biological Problems

Document Type : Original Research Article

Author

Elham Mahdavi

Department of Electrical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran

10.22034/apj.2025.730012
Abstract
Quantum genetic algorithm, which is a combination of quantum mechanics principles and evolutionary algorithms, has been proposed as a new method in the field of optimization. In recent years, numerous applications of these algorithms have been reported in solving complex biological problems such as gene and stem cell structure analysis, protein simulation, and molecular behavior prediction. This article aims to comprehensively review the performance of quantum genetic algorithm in biological problems, and reviews its theoretical foundations, functions, advantages, and challenges. Various studies have shown that quantum genetic algorithm, by utilizing quantum properties such as superposition and entanglement, has been able to improve the inefficient convergence problems of classical algorithms and provide more optimal solutions. Also, in the second part of the article, the architecture and technical mechanisms of quantum genetic algorithm are described and applied examples in biology are analyzed. Finally, the prospects of this technology in biological research are reflected by providing recommendations and perspectives for future developments.

Keywords

Quantum Genetic Algorithm
Biological Simulation
DNA Structure Problem
Quantum Mechanics
Biological Optimization
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