Indexed by:
期刊论文
First Author:
Liu, Haitao
Correspondence Author:
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.
Co-author:
Xu, Shengli,Chen, Xudong,Wang, Xiaofang,Ma, Qingchao
Date of Publication:
2017-01-01
Journal:
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Included Journals:
SCIE、EI、Scopus
Document Type:
J
Volume:
55
Issue:
1
Page Number:
155-177
ISSN No.:
1615-147X
Key Words:
Constrained global optimization; DIRECT-type constraint-handling;
Adaptive metamodeling
Abstract:
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.
Translation or Not:
no
