期刊
2018 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
卷 -, 期 -, 页码 765-771出版社
IEEE
DOI: 10.1109/CEC.2018.8477908
关键词
univariate sampling; evolution strategy; multi modal nonseparable problems
类别
资金
- Ministry of Science and Technology (MOST) of China [2017YFC0804003]
- National Science Foundation of China [K17271004]
- Science and Technology Innovation Committee Foundation of Shenzhen [ZDSYS201703031748284]
This paper proposes an evolution strategy (ES) algorithm called hybrid sampling-evolution strategy (HS-ES) that combines the covariance matrix adaptation-evolution strategy (CMA-ES) and univariate sampling method. In spite that the univariate sampling has been widely thought as a method only to separable problems, the analysis and experimental tests show that it is actually very effective for solving multimodal nonseparable problems. As the univariate sampling is a complementary algorithm to the CMA-ES which has obvious advantages for solving unimodal nonseparable problems, the proposed HS-ES tries to take advantages of these two algorithms to improve its searching performance. Experimental results on CEC-2018 demonstrate the effectiveness of the proposed HS-ES.
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