For networks with fixed network topology, when the total coupling strength between nodes is limited and the coupling strength between nodes is saturated, the global optimization algorithms including genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are used to adjust the coupling strength between nodes to improve the synchronizability of the network, respectively. Simulation results show that in WS small-world network, when the edge betweenness centrality of the edge is large, the coupling strength of the edge after optimization is greater. Furthermore, compared with GA, PSO has better performance.

中文翻译：

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耦合强度饱和的复杂网络的最优同步性

对于网络拓扑结构固定的网络，当节点间总耦合强度有限且节点间耦合强度饱和时，采用遗传算法（GA）和粒子群优化（PSO）算法等全局优化算法调整耦合强度节点之间分别提高网络的同步性。仿真结果表明，在WS小世界网络中，当边的边介数中心性较大时，优化后边的耦合强度较大。此外，与 GA 相比，PSO 具有更好的性能。