Robust and multi-objective optimization applied in I-beam using nondominated sorting genetic algorithm
The I-beam problem is a multi-objective optimization which originally consists of minimizing the cross-sectional area and the vertical deflection of the beam. When uncertainty is considered in the production of the beam, the I-beam problem becomes a robust optimization problem where the mean and var...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2009
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/9199 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | The I-beam problem is a multi-objective optimization which originally consists of minimizing the cross-sectional area and the vertical deflection of the beam. When uncertainty is considered in the production of the beam, the I-beam problem becomes a robust optimization problem where the mean and variance of a sample around the neighborhood of a solution are taken as the objective functions. In this paper, we present robust optimization applied in I-beam using Nondominated Sorting Genetic Algorithm (NSGA). While the main objective of the optimization is to find the robust optimum cross-sectional area of the beam, we parameterize the NSGA for the optimization of other objective functions such as the beam deflection and bending stress. |
|---|