Recent advances in particle swarm

By Xiaohui Hu, Yuhui Shi, R. Eberhart. Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 2004

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Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems (2008, methodology): “This algorithm has been recently applied to power systems as well as adaptive control applications [76], [77].”
Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review (2017, background): “already (Banks et al., 2007, 2008; Hu et al., 2004; Parsopoulos and Vrahatis, 2002b; Poli, 2008; Poli, Kennedy, et al., 2007; Song and Gu, 2004), there are two important reasons for an additional review paper:”
Enhancing particle swarm optimization using generalized opposition-based learning (2011, methodology): “PSO is a population-based search algorithm that starts with an initial population of randomly generated particles [16].”
A discrete version of particle swarm optimization for flowshop scheduling problems (2007, background): “All the related research has totaled over 300 papers until 2004 [2].”
Economic Allocation for Energy Storage System Considering Wind Power Distribution (2015, methodology): “In order to improve the efficiency and accuracy, a linearly decreasing inertia weight frommaximum value to minimum is applied to update the inertia weight [19]”