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

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• 作者：Haitao Liu ; Shengli Xu ; Xudong Chen…
• 关键词：Constrained global optimization ; DIRECT ; type constraint ; handling ; Adaptive metamodeling
• 刊名：Structural and Multidisciplinary Optimization
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：55
• 期：1
• 页码：155-177
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Theoretical and Applied Mechanics; Computational Mathematics and Numerical Analysis; Engineering Design;
• 出版者：Springer Berlin Heidelberg
• ISSN：1615-1488
• 卷排序：55

文摘

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.