Fuzzy Hierarchical Surrogate Assists Probabilistic Particle Swarm Optimization for expensive high dimensional problem

作者：

Highlights：

• Use FCM to classify with the training set and construct FSA models respectively.

• FSA, LSA, and GSA models are proposed for the first time to form the FHSA model.

• The FHSA model is used to combine with the PPSO to solve the expensive problem.

摘要

•Use FCM to classify with the training set and construct FSA models respectively.•FSA, LSA, and GSA models are proposed for the first time to form the FHSA model.•The FHSA model is used to combine with the PPSO to solve the expensive problem.

论文关键词：Surrogate-assisted,Probabilistic PSO,Fuzzy Clustering,Meta-heuristic evolutionary algorithm

论文评审过程：Received 30 December 2020, Revised 24 February 2021, Accepted 6 March 2021, Available online 10 March 2021, Version of Record 18 March 2021.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.106939