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 |
| ISSN | 0305-215X 1029-0273 |
| DOI | 10.1080/0305215X.2010.512085 |
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| Abstract | 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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| AbstractList | 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. 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. [PUBLICATION ABSTRACT] |
| Author | Djikpéssé, Hugues Wilkinson, David Couët, Benoît |
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| Cites_doi | 10.1137/S105262340138983X 10.1109/4235.873238 10.1007/978-3-642-48320-2 10.1109/TIM.2009.2025684 10.1109/TEVC.2003.817236 10.1111/j.1365-2478.2006.00551.x 10.1017/CBO9781139171502 10.1029/RG020i002p00219 10.1007/s101070100244 10.1109/TEVC.2005.850256 10.1515/9781400830176 10.1162/evco.1999.7.1.19 10.1190/1.1444611 10.1002/0471722138 10.2118/87026-PA 10.1137/S105262340038081X 10.1137/S003614450242889 10.1093/comjnl/7.4.308 |
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| SubjectTerms | Aggregates Classification Computational efficiency derivative-free optimization expensive simulation-based constraints Mathematical analysis Mathematical functions Mathematical models Mathematical problems oilfield-production optimization Optimization Optimization algorithms Order disorder sequential lexicographic comparison Simulation Simulators Studies |
| Title | A practical sequential lexicographic approach for derivative-free black-box constrained optimization |
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