TY  - EJOU
AU  - Bali, Malvinder Singh 
AU  - Jiang, Weiwei 
AU  - Verma, Saurav 
AU  - Kour, Kanwalpreet 
AU  - Rao, Ashwini 

TI  - Optimizing Resource Allocation in Blockchain Networks Using Neural Genetic Algorithm
T2  - Computers, Materials \& Continua

PY  - 2026
VL  - 86
IS  - 2
SN  - 1546-2226

AB  - In recent years, Blockchain Technology has become a paradigm shift, providing Transparent, Secure, and Decentralized platforms for diverse applications, ranging from Cryptocurrency to supply chain management. Nevertheless, the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency, scalability, and energy consumption. This study proposes an innovative approach to Blockchain network optimization, drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms. Specifically, we explore the application of genetic algorithms, particle swarm optimization, and related evolutionary techniques to enhance the performance of blockchain networks. The proposed methodologies aim to optimize consensus mechanisms, improve transaction throughput, and reduce resource consumption. Through extensive simulations and real-world experiments, our findings demonstrate significant improvements in network efficiency, scalability, and stability. This research offers a thorough analysis of existing optimization techniques, introduces novel strategies, and assesses their efficacy based on empirical outputs.
KW  - Blockchain technology; energy efficiency; environmental impact; evolutionary algorithms; optimization

DO  - 10.32604/cmc.2025.070866