A social learning particle swarm optimization algorithm for scalable optimization

By Ran Cheng, Yaochu Jin. Information Sciences, 2015

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Position-Transitional Particle Swarm Optimization-Incorporated Latent Factor Analysis (2022, background): “Meanwhile, a PSO algorithm further has the advantages of high efficiency and compatibility [32 ‐ 34 , 53 ‐ 59 ].”
Feature selection for high-dimensional classification using a competitive swarm optimizer (2016, methodology): “Very recently, Cheng and Jin have proposed a PSO variant, known as competitive swarm optimizer (CSO), for large-scale optimization (Cheng and Jin 2015).”
Imitation Learning (2017, background): “A social variation of PSO is introduced in Cheng and Jin [2015], inspired by animals learning in nature from observing their peers.”
Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive Problems (2017, methodology): “The SA-COSO consists of two cooperative PSO variants, one being a PSO with a constriction factor [52] and the other a social learning-based PSO (SL-PSO) [53].”
A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization (2018, background): “While large-scale optimization has already attracted certain interests in the single-objective literature [56]–[62], the development of large-scale multiobjective optimization is still in the infancy [63].”