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

• Main Authors: Dumas, Laurent, Soriano, Jaymar B.
• Format: text
• Published: Animo Repository 2009
• Subjects: Combinatorial optimization; Evolutionary computation; Genetic algorithms; Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/9199
• Institution: De La Salle University

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.