A Combined Algorithm for Solving Reliability-based Robust Design Optimization Problems
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Authors
Ameneh Forouzandeh Shahraki
- Ameneh Forouzandeh Shahraki, University of Science and Technology.
Rassoul Noorossana
- University of Science and Technology.
Abstract
In the most of the design optimization problems, we encounter uncertainties in design variables and problem parameters. In these problems, robustness and reliability of design are so important. Both robust design and reliability-based design approaches take into consideration these aspects. However, the individual application of them doesn’t ensure the stability of product during its life cycle. In this paper, we combine both robust design and reliability-based design approaches into one model and propose a genetic and reliability analysis combined algorithm to solve this kind of problem. Moreover, to increase the efficiency of the genetic algorithm, we use the design of experiment (DOE) to find the optimal levels of the parameters of this algorithm. The application of the proposed methodology is demonstrated using a numerical example.
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ISRP Style
Ameneh Forouzandeh Shahraki, Rassoul Noorossana, A Combined Algorithm for Solving Reliability-based Robust Design Optimization Problems, Journal of Mathematics and Computer Science, 7 (2013), no. 1, 54 - 62
AMA Style
Shahraki Ameneh Forouzandeh, Noorossana Rassoul, A Combined Algorithm for Solving Reliability-based Robust Design Optimization Problems. J Math Comput SCI-JM. (2013); 7(1):54 - 62
Chicago/Turabian Style
Shahraki, Ameneh Forouzandeh, Noorossana, Rassoul. "A Combined Algorithm for Solving Reliability-based Robust Design Optimization Problems." Journal of Mathematics and Computer Science, 7, no. 1 (2013): 54 - 62
Keywords
- Reliability
- robustness
- multi-objective optimization
- genetic algorithm
- design of experiment
MSC
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