| Full text | |
| Author(s): Show less - |
Guirguis, David
[1, 2]
;
Aulig, Nikola
[3]
;
Picelli, Renato
[4]
;
Zhu, Bo
[5]
;
Zhou, Yuqing
[6]
;
Vicente, William
[7]
;
Iorio, Francesco
[8]
;
Olhofer, Markus
[3]
;
Matusiks, Wojciech
[5]
;
Coello Coello, Carlos Artemio
[9]
;
Saitou, Kazuhiro
[6]
Total Authors: 11
|
| Affiliation: | [1] Univ Michigan, Ann Arbor, MI 48109 - USA
[2] Univ Toronto, Toronto, ON M5S 3G4 - Canada
[3] Honda Res Inst Europe GmbH, D-63073 Offenbach - Germany
[4] Univ Sao Paulo, Dept Min & Petr Engn, Polytech Sch, BR-05508010 Sao Paulo - Brazil
[5] MIT, CSAIL, 77 Massachusetts Ave, Cambridge, MA 02139 - USA
[6] Univ Michigan, Dept Mech Engn, Ann Arbor, MI 48109 - USA
[7] Univ Estadual Campinas, Sch Agr Engn, BR-13083875 Campinas - Brazil
[8] Autodesk Res, Toronto, ON M5G 1M1 - Canada
[9] IPN, CINVESTAV, Dept Comp, Evolutionary Computat Grp, Mexico City 07360, DF - Mexico
Total Affiliations: 9
|
| Document type: | Journal article |
| Source: | IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION; v. 24, n. 4, p. 613-633, AUG 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
Black-box topology optimization (BBTO) uses evolutionary algorithms and other soft computing techniques to generate near-optimal topologies of mechanical structures. Although evolutionary algorithms are widely used to compensate the limited applicability of conventional gradient optimization techniques, methods based on BBTO have been criticized due to numerous drawbacks. In this article, we discuss topology optimization as a black-box optimization problem. We review the main BBTO methods, discuss their challenges and present approaches to relax them. Dealing with those challenges effectively can lead to wider applicability of topology optimization, as well as the ability to tackle industrial, highly constrained, nonlinear, many-objective, and multimodal problems. Consequently, future research in this area may open the door for innovating new applications in science and engineering that may go beyond solving classical optimization problems of mechanical structures. Furthermore, algorithms designed for BBTO can be added to existing software toolboxes and packages of topology optimization. (AU) | |
| FAPESP's process: | 18/05797-8 - Addressing design challenges of offshore structures via Multiphysics topology optimization |
| Grantee: | Renato Picelli Sanches |
| Support Opportunities: | Research Grants - Young Investigators Grants |