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Constrained global optimization via a DIRECT-type constraint-handling technique and an adaptive metamodeling strategy

发表时间:2019-03-12
点击次数:
论文类型:
期刊论文
第一作者:
Liu, Haitao
通讯作者:
Xu, SL; Wang, XF (reprint author), Dalian Univ Technol, Sch Energy & Power Engn, Dalian, Peoples R China.; Xu, SL; Wang, XF (reprint author), Minist Educ, Key Lab Ocean Energy Utilizat & Energy Conservat, Dalian, Peoples R China.
合写作者:
Xu, Shengli,Chen, Xudong,Wang, Xiaofang,Ma, Qingchao
发表时间:
2017-01-01
发表刊物:
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
收录刊物:
SCIE、EI、Scopus
文献类型:
J
卷号:
55
期号:
1
页面范围:
155-177
ISSN号:
1615-147X
关键字:
Constrained global optimization; DIRECT-type constraint-handling; Adaptive metamodeling
摘要:
Recent metamodel-based global optimization algorithms are very promising for box-constrained expensive optimization problems. However, few of them can tackle constrained optimization problems. This article presents an improved constrained optimization algorithm, called eDIRECT-C, for expensive constrained optimization problems. In the eDIRECT-C algorithm, we present a novel DIRECT-type constraint-handling technique that separately handles feasible and infeasible cells. This technique has no user-defined parameter and is beneficial for exploring the undetected feasible regions and boundary of feasible regions. We also employ an adaptive metamodeling strategy to build appropriate metamodel types for objective and constraints respectively. This strategy yields more accurate predictions and therefore significantly speeds up the convergence. To assess the performance of eDIRECT-C, we compare it with some state-of-the-art metamodel-based constrained optimization algorithms and the original DIRECT algorithm on 13 benchmark problems and 4 engineering examples. The comparative results imply that the proposed algorithm is very promising for constrained problems in terms of the convergence speed, quality of final solutions and success rate.
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