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Synchronous Gravitational Search Algorithm vs Asynchronous Gravitational Search Algorithm: A Statistical Analysis

机译:同步引力搜索算法与异步引力搜索算法的统计分析

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Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. It stems from Newtonian law of gravity and motion. The performance of synchronous GSA (S-GSA) and asynchronous GSA (A-GSA) is studied here using statistical analysis. The agents in S-GSA are updated synchronously, where the whole population is updated after each member's performance is evaluated. On the other hand, an agent in A-GSA is updated immediately after its performance evaluation. Hence an agent in A-GSA is updated without the need to synchronize with the entire population. Asynchronous update is more attractive from the perspective of parallelization. The results show that both implementations have similar performance.
机译:引力搜索算法(GSA)是群体智能算法的新成员。它源于牛顿的重力和运动定律。本文使用统计分析研究了同步GSA(S-GSA)和异步GSA(A-GSA)的性能。 S-GSA中的代理会同步更新,其中在评估每个成员的绩效后更新总体。另一方面,A-GSA中的代理在评估其性能后立即进行更新。因此,A-GSA中的代理无需与整个总体同步就可以更新。从并行化的角度来看,异步更新更具吸引力。结果表明,两种实现都有相似的性能。

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