On-line Search History-assisted Restart Strategy for Covariance Matrix Adaptation Evolution Strategy

Yang Lou, Shiu Yin Yuen, Guanrong Chen, Xin Zhang

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Restart strategy helps the covariance matrix adaptation evolution strategy (CMA-ES) to increase the probability of finding the global optimum in optimization, while a single run CMA-ES is easy to be trapped in local optima. In this paper, the continuous non-revisiting genetic algorithm (cNrGA) is used to help CMA-ES to achieve multiple restarts from different sub-regions of the search space. The CMA-ES with on-line search history-assisted restart strategy (HR-CMA-ES) is proposed. The entire on-line search history of cNrGA is stored in a binary space partitioning (BSP) tree, which is effective for performing local search. The frequently sampled sub-region is reflected by a deep position in the BSP tree. When leaf nodes are located deeper than a threshold, the corresponding sub-region is considered a region of interest (ROI). In HR-CMA-ES, cNrGA is responsible for global exploration and suggesting ROI for CMA-ES to perform an exploitation within or around the ROI. CMA-ES restarts independently in each suggested ROI. The non-revisiting mechanism of cNrGA avoids to suggest the same ROI for a second time. Experimental results on the CEC 2013 and 2017 benchmark suites show that HR-CMA-ES performs better than both CMA-ES and cNrGA. A positive synergy is observed by the memetic cooperation of the two algorithms.

原文English
主出版物標題2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面3142-3149
頁數8
ISBN(電子)9781728121536
DOIs
出版狀態Published - 6月 2019
事件2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand
持續時間: 10 6月 201913 6月 2019

出版系列

名字2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

Conference

Conference2019 IEEE Congress on Evolutionary Computation, CEC 2019
國家/地區New Zealand
城市Wellington
期間10/06/1913/06/19

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