Feasibility Analysis of the Use of Metaheuristic Algorithms as Miners in Blockchain Networks
Abstract
Proof-of-Work (PoW) mining in blockchains consumes large amounts of energy on intensive hash computations without generating practical value. As an alternative, this study investigates the use of metaheuristics — Genetic Algorithm, Simulated Annealing, and Particle Swarm Optimization (PSO) — in a mining model that solves useful computational problems, such as the Traveling Salesman Problem, where valid hashes represent solutions. Results indicate that Simulated Annealing efficiently found good solutions. The Genetic Algorithm was functional but incurred high computational costs, while PSO showed inferior performance. Despite its potential, metaheuristic-based mining still faces challenges regarding its feasibility and practical application in blockchain systems.
Keywords:
Blockchains, Distributed Ledger, Combinatorial optimization
References
Antonopoulos, A. M. (2014). Mastering Bitcoin: Unlocking Digital Crypto-Currencies. O’Reilly Media, Inc., 1st edition.
Asif, R., & Hassan, S. (2023). Shaping the future of Ethereum: Exploring energy consumption in proof-of-work and proof-of-stake consensus. Frontiers in Blockchain, 6.
Ball, M., Rosen, A., Sabin, M., & Vasudevan, P. N. (2017). Proofs of useful work. IACR Cryptology ePrint Archive, 2017:203. Accessed: Jun. 29, 2017.
Belotti, M., Božić, N., Pujolle, G., & Secci, S. (2019). A vademecum on blockchain technologies: When, which, and how. IEEE Communications Surveys & Tutorials, 21(4), 3796–3838.
Bizzaro, F., Conti, M., & Pini, M. S. (2020). Proof of evolution: Leveraging blockchain mining for a cooperative execution of genetic algorithms. In 2020 IEEE International Conference on Blockchain (Blockchain) (pp. 450–455).
Blum, C., & Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys, 35(3), 268–308.
de Vries, A. (2018). Bitcoin’s growing energy problem. Energy Policy, 2, 801–805.
Gaspar-Cunha, A., Takahashi, R., & Antunes, C. (2012). Manual de computação evolutiva e metaheurística. Ensino. Imprensa da Universidade de Coimbra / Coimbra University Press.
Greve, F., Sampaio, L., Abijaude, J., Coutinho, A. A., Brito, I., & Queiroz, S. (2018). Blockchain e a Revolução do Consenso sob Demanda. Revista de Informação, Tecnologia e Sociedade, 30.
Halford, R. (2014). Gridcoin: Crypto-currency using Berkeley Open Infrastructure Network Computing Grid as a proof of work. Online.
Kennedy, J., & Eberhart, R. C. (1995). Particle swarm optimization. In Proceedings of the IEEE International Conference on Neural Networks (pp. 1942–1948).
King, S. (2013). Primecoin: Cryptocurrency with prime number proof-of-work. [link]
Lashkari, B., & Musilek, P. (2021). A comprehensive review of blockchain consensus mechanisms. IEEE Access, 9, 43620–43652.
Miah, M. S. U., Rahman, M., Hossain, M. S., & Rupai, A. (2019). Introduction to Blockchain.
Shibata, N. (2019). Proof-of-search: Combining blockchain consensus formation with solving optimization problems. IEEE Access, 7, 172994–173006.
Asif, R., & Hassan, S. (2023). Shaping the future of Ethereum: Exploring energy consumption in proof-of-work and proof-of-stake consensus. Frontiers in Blockchain, 6.
Ball, M., Rosen, A., Sabin, M., & Vasudevan, P. N. (2017). Proofs of useful work. IACR Cryptology ePrint Archive, 2017:203. Accessed: Jun. 29, 2017.
Belotti, M., Božić, N., Pujolle, G., & Secci, S. (2019). A vademecum on blockchain technologies: When, which, and how. IEEE Communications Surveys & Tutorials, 21(4), 3796–3838.
Bizzaro, F., Conti, M., & Pini, M. S. (2020). Proof of evolution: Leveraging blockchain mining for a cooperative execution of genetic algorithms. In 2020 IEEE International Conference on Blockchain (Blockchain) (pp. 450–455).
Blum, C., & Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys, 35(3), 268–308.
de Vries, A. (2018). Bitcoin’s growing energy problem. Energy Policy, 2, 801–805.
Gaspar-Cunha, A., Takahashi, R., & Antunes, C. (2012). Manual de computação evolutiva e metaheurística. Ensino. Imprensa da Universidade de Coimbra / Coimbra University Press.
Greve, F., Sampaio, L., Abijaude, J., Coutinho, A. A., Brito, I., & Queiroz, S. (2018). Blockchain e a Revolução do Consenso sob Demanda. Revista de Informação, Tecnologia e Sociedade, 30.
Halford, R. (2014). Gridcoin: Crypto-currency using Berkeley Open Infrastructure Network Computing Grid as a proof of work. Online.
Kennedy, J., & Eberhart, R. C. (1995). Particle swarm optimization. In Proceedings of the IEEE International Conference on Neural Networks (pp. 1942–1948).
King, S. (2013). Primecoin: Cryptocurrency with prime number proof-of-work. [link]
Lashkari, B., & Musilek, P. (2021). A comprehensive review of blockchain consensus mechanisms. IEEE Access, 9, 43620–43652.
Miah, M. S. U., Rahman, M., Hossain, M. S., & Rupai, A. (2019). Introduction to Blockchain.
Shibata, N. (2019). Proof-of-search: Combining blockchain consensus formation with solving optimization problems. IEEE Access, 7, 172994–173006.
Published
2025-05-19
How to Cite
ROSA, Luiz Felipe Fonseca; RODRIGUES, Luiz Antonio; BRUN, André Luiz.
Feasibility Analysis of the Use of Metaheuristic Algorithms as Miners in Blockchain Networks. In: BLOCKCHAIN WORKSHOP: THEORY, TECHNOLOGY AND APPLICATIONS (WBLOCKCHAIN), 8. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 210-223.
DOI: https://doi.org/10.5753/wblockchain.2025.9533.
