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人群搜索算法(SOA)结合人的思维习惯和行为方式,克服了粒子群算法(PSO)和遗传算法(GA)等智能优化算法收敛性差、局部寻优的缺点。建立以体积最小为目标的多约束数学模型,提出了SOA算法的圆柱齿轮减速器的优化设计方法,同PSO算法、GA算法的仿真结果进行对比分析,SOA算法的收敛速度更快、全局搜索能力更强和鲁棒性更好,为机械部件优化设计提供了参考。
Crowd search algorithm (SOA) overcomes the shortcomings of poor convergence and local optimization of intelligent optimization algorithms, such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), combined with people’s thinking habit and behavior. A multi-constrained mathematic model aimed at the minimum volume is established. The optimization design method of cylinder gear reducer with SOA algorithm is proposed. Comparing with the simulation results of PSO algorithm and GA algorithm, the convergence speed of SOA algorithm is faster and the global search ability Stronger and more robust, which provides a reference for the optimization design of mechanical components.