A Bilevel Methodology for solving a Structural Optimization Problem with both Continuous and Categorical Variables
Author(s) -
Pierre-Jean Barjhoux,
Youssef Diouane,
Stéphane Grihon,
Dimitri Bettebghor,
Joseph Morlier
Publication year - 2018
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2018-3579
Subject(s) - bilevel optimization , categorical variable , computer science , mathematical optimization , optimization problem , mathematics , algorithm , machine learning
In industrial structural optimization problems, two kinds of variables are involved : continuous variables, like geometrical parameters, and categorical variables like choices of material and cross-sectional shapes. A key difficulty of this kind of problem is the sensitivity of the computation cost with respect to the number of categorical design variables. In this article, a new methodology is proposed to address this mixed continuous-categorical structural optimization problem. For this purpose, a 10-bar truss test case representative for industrial design is introduced. Promising results have been obtained in terms of computation cost, compared to approaches based on combinatorial algorithms.
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