A ground-structure-based representation with an element-removal algorithm for truss topology optimization
In this study, a new ground-structure-based representation for truss topology optimization is proposed. The proposed representation employs an algorithm that removes unwanted elements from trusses to obtain the final trusses. These unwanted elements include kinematically unstable elements and useless zero-force elements. Since the element-removal algorithm is used in the translation of representation codes into corresponding trusses, this results in more representation codes in the search space that are mapped into kinematically stable and efficient trusses. Since more representation codes in the search space represent stable and efficient trusses, the strategy increases meaningful competition among representation codes. This remapping strategy alleviates the problem of having large search spaces using ground structures, and encourages faster convergences. To test the effectiveness of the proposed representation, it is used with a simple multi-population particle swarm optimization algorithm to solve several truss topology optimization problems. It is found that the proposed representation can significantly improve the performance of the optimization process.
KeywordsTruss topology optimization Representation Remapping Kinematic stability Zero-force element Element removal Particle swarm optimization Multiple populations
The authors are grateful to the Thailand Research Fund for the financial support for this study (Contract Number: RMU5380026). A scholarship under the Graduate Scholarship Program for Excellent Foreign Students by Sirindhorn International Institute of Technology (SIIT) for the first author is greatly appreciated.
- Bołbotowski K, Sokół T (2016) New method of generating Strut and Tie models using truss topology optimization. In: Advances in Mechanics: Theoretical, Computational and Interdisciplinary Issues - 3rd Polish Congress of Mechanics, PCM 2015 and 21st International Conference on Computer Methods in Mechanics, CMM 2015, CRC Press/Balkema, Gdansk, 8–11 September 2015Google Scholar
- Eberhart RC, Shi Y (2000) Comparing inertia weights and constriction factors in particle swarm optimization. In: Proceedings of the 2000 Congress on Evolutionary Computation, CEC 2000, IEEE Computer Society, San Diego, 16–19 July 2000Google Scholar
- Rajan SD (1995) Sizing, shape, and topology design optimization of trusses using genetic algorithm. J Struct Eng 121(10):1480–1487. https://doi.org/10.1061/(ASCE)0733-9445(1995)121:10(1480) CrossRefGoogle Scholar