A practical sequential lexicographic approach for derivative-free black-box constrained optimization
Many engineering optimization problems involve models that might not exhibit the necessary smoothness to warrant efficient use of gradient algorithms. Many of these problems are also subject to constraints that might be simulation-based and as costly to compute as the objective function. Traditional...
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Published in | Engineering optimization Vol. 43; no. 7; pp. 721 - 739 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Taylor & Francis
01.07.2011
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Many engineering optimization problems involve models that might not exhibit the necessary smoothness to warrant efficient use of gradient algorithms. Many of these problems are also subject to constraints that might be simulation-based and as costly to compute as the objective function. Traditionally, such problems are solved using either penalty methods or lexicographic ordering that evaluates aggregate constraints prior to computing objective values. This study describes a cost-effective approach to performing such optimizations. After classifying all constraints depending on their computational cost, points not satisfying linear constraints are feasibilized, and a suitable penalty term constructed. A sequential lexicographic ordering is then applied in which inexpensive nonlinear constraints take precedence over expensive ones, which in turn take precedence over objective function values. The performance advantage of the proposed method over traditional ones is demonstrated with a set of analytical test problems, and with oilfield-production optimization examples that use 'black-box' simulators. |
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Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 |
ISSN: | 0305-215X 1029-0273 |
DOI: | 10.1080/0305215X.2010.512085 |