Asynchronous Particular Swarm Optimization

M. Ordukaya
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Abstract

In this paper.we present particle swarm optimization based on asynchronous algorithms for a multi-agent swarm.We study generalized PSO algoritm with two schemes called global best (gbest) and local best (lbest).We apply these two schemes to our multimodel function.Generally PSO is performed with synchronous algorithms.Our corparative study indicates that PSO modelled with asynchronous algorithm converges to a real desired value as synchronous models.
异步特定群优化
在本文中。提出了一种基于异步算法的多智能体群体粒子群优化算法。研究了具有全局最优和局部最优两种方案的广义粒子群算法。我们将这两种格式应用于我们的多模型函数。一般采用同步算法实现粒子群优化。我们的比较研究表明,采用异步算法建模的粒子群与同步模型一样收敛于一个真实的期望值。
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