Robust and multi-objective optimization applied in I-beam using nondominated sorting genetic algorithm

College

College of Science

Department/Unit

Mathematics and Statistics Department

Document Type

Archival Material/Manuscript

Publication Date

2009

Abstract

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.

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Disciplines

Mathematics

Keywords

Combinatorial optimization; Evolutionary computation; Genetic algorithms

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