论文标题
粒子群的优化：使用N-形式的稳定性分析在任意系数分布下
Particle Swarm Optimization: Stability Analysis using N-Informers under Arbitrary Coefficient Distributions
论文作者
论文摘要
本文在最小的建模假设下得出了一种易于使用定理的订单$ 1 $和订单 - $ 2 $ $ 2 $的稳定性标准，用于公共类别的粒子群优化（PSO）变体。具体而言，可以将粒子位置和群体线人之间随机加权差异向量的有限差的PSO变体覆盖。此外，使用该定理的使用允许PSO实践者获得对控制系数之间关系的稳定标准。在社会和认知控制系数相等的限制下，几乎所有以前的PSO稳定结果都提供了稳定标准。使用派生定理时，这种限制不存在。使用派生的定理，作为其易用性的证明，稳定性标准是衍生得出的，而不会对三个流行PSO变体的控制系数之间的关系施加限制。
This paper derives, under minimal modelling assumptions, a simple to use theorem for obtaining both order-$1$ and order-$2$ stability criteria for a common class of particle swarm optimization (PSO) variants. Specifically, PSO variants that can be rewritten as a finite sum of stochastically weighted difference vectors between a particle's position and swarm informers are covered by the theorem. Additionally, the use of the derived theorem allows a PSO practitioner to obtain stability criteria that contains no artificial restriction on the relationship between control coefficients. Almost all previous PSO stability results have provided stability criteria under the restriction that the social and cognitive control coefficients are equal; such restrictions are not present when using the derived theorem. Using the derived theorem, as demonstration of its ease of use, stability criteria are derived without the imposed restriction on the relation between the control coefficients for three popular PSO variants.
