@inproceedings{8d617a3b6f4441e886d5c028497e7d81,
title = "A Comparison Study of Surrogate Model Based Preselection in Evolutionary Optimization",
abstract = "In evolutionary optimization, the purpose of preselection is to identify some promising solutions in a set of candidate offspring solutions. The surrogate model is a popular method employed in preselection. A surrogate model is built to approximate the original objective function and to estimate the fitness values of the candidate solutions. Based on the estimated fitness values, the promising solutions can be identified. This paper aims to study and compare the surrogate model based preselection strategies in evolutionary algorithms. Systematic experiments are conducted to study the performance of four surrogate models. The experimental results suggest the surrogate model based preselection can significantly improve the performance of evolutionary algorithms.",
keywords = "Evolutionary algorithm, Preselection, Surrogate model",
author = "Hao Hao and Jinyuan Zhang and Aimin Zhou",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 14th International Conference on Intelligent Computing, ICIC 2018 ; Conference date: 15-08-2018 Through 18-08-2018",
year = "2018",
doi = "10.1007/978-3-319-95933-7\_80",
language = "英语",
isbn = "9783319959320",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "717--728",
editor = "De-Shuang Huang and Kang-Hyun Jo and Xiao-Long Zhang",
booktitle = "Intelligent Computing - 14th International Conference, ICIC 2018, Proceedings",
address = "德国",
}