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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.11667 |
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| _version_ | 1866918443429658624 |
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| author | Junior, Romeu Rossi Nacif, José Augusto Miranda Souza, Leonardo Antônio Mendes Mendes, Marcus Henrique Soares |
| author_facet | Junior, Romeu Rossi Nacif, José Augusto Miranda Souza, Leonardo Antônio Mendes Mendes, Marcus Henrique Soares |
| contents | This work investigates the performance of a Hybrid Quantum Genetic Algorithm (HQGA) compared to a classical Genetic Algorithm (GA) for solving the portfolio optimization problem. Our results indicate that the HQGA converges faster to the optimal solution than its classical counterpart, while also maintaining a higher level of population diversity throughout the optimization process. In addition, the HQGA requires significantly fewer evaluations-to-solution than a brute-force approach to reach the global optimum. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_11667 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Comparative Study of Hybrid Quantum and Classical Genetic Algorithms in Portfolio Optimization Junior, Romeu Rossi Nacif, José Augusto Miranda Souza, Leonardo Antônio Mendes Mendes, Marcus Henrique Soares Quantum Physics This work investigates the performance of a Hybrid Quantum Genetic Algorithm (HQGA) compared to a classical Genetic Algorithm (GA) for solving the portfolio optimization problem. Our results indicate that the HQGA converges faster to the optimal solution than its classical counterpart, while also maintaining a higher level of population diversity throughout the optimization process. In addition, the HQGA requires significantly fewer evaluations-to-solution than a brute-force approach to reach the global optimum. |
| title | A Comparative Study of Hybrid Quantum and Classical Genetic Algorithms in Portfolio Optimization |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2604.11667 |