Industry and research communities have widely studied Blockchain technology, and the consortium blockchain is currently the most used category with a wide range of applications. However, issues, such as the performance of consensus mechanisms, have become essential constraints on promoting and applying the consortium blockchain. To improve the performance of the consortium blockchain consensus, we use the practical Byzantine fault tolerance (PBFT) consensus widely used in consortium blockchains to reduce the number of consensus nodes to optimize performance. Using the PBFT consensus, we screen high-performance nodes and obtain a reliable and limited number of consensus nodes. We propose a genetic algorithm-based blockchain consensus algorithm improvement scheme, design the fitness function of blockchain nodes and the genetic algorithm to iterate out consensus node groups with excellent indicators continuously, and finally iterate the nodes participating in the consensus. This algorithm can increase the speed and efficiency of the consensus, block generation, and computation. The algorithm in this article is tested on the FISCO BCOS (i.e., a consortium blockchain platform built by the FISCO open-source working group), and controlled experiments and the experimental results illustrate the safety and practicability of the method.

产业界和研究界广泛研究区块链技术，联盟链是目前使用最多的一类，应用范围广泛。然而，共识机制的性能等问题已经成为联盟链推广应用的本质制约因素。为了提高联盟链共识的性能，我们使用联盟链广泛使用的实用拜占庭容错（PBFT）共识来减少共识节点的数量来优化性能。使用PBFT共识，筛选高性能节点，获得可靠且数量有限的共识节点。我们提出了一种基于遗传算法的区块链共识算法改进方案，设计区块链节点的适应度函数和遗传算法，不断迭代出指标优异的共识节点组，最终迭代参与共识的节点。该算法可以提高共识、块生成和计算的速度和效率。本文算法在FISCO BCOS（即FISCO开源工作组打造的联盟链平台）上进行了测试，并进行了对照实验，实验结果说明了该方法的安全性和实用性。