Collaborative Optimization Computation Using Improved Genetic Algorithm and ANSYS
- https://doi.org/10.2991/icadme-15.2015.343How to use a DOI?
- Lagrange multiplier method; discrete variables; improved genetic algorithm; ANSYS; optimization design;
Aiming at the problems that it is difficult to calculate and establish accurate mathematical model in the structure optimization with discrete variables, the Lagrange multiplier method is proposed to deal with the constrain conditions in the improved genetic algorithm which solved the problems of “premature” and low efficiency in the simple genetic algorithm. The improved genetic algorithm is achieved by MATLAB, and it invoked the ANSYS software to conduct finite element calculations and data exchange. This collaborative algorithm is verified by two truss examples in this paper. Compared with other research results, the collaborative optimization computation using improved genetic algorithm and ANSYS based on Lagrange multiplier method can get better global optimal solution, and it also has high accuracy and good reliability.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Qi Wang AU - Houan Ding AU - Yuxiang Lin AU - Yue Luo PY - 2015/10 DA - 2015/10 TI - Collaborative Optimization Computation Using Improved Genetic Algorithm and ANSYS BT - Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering PB - Atlantis Press SP - 1859 EP - 1864 SN - 2352-5401 UR - https://doi.org/10.2991/icadme-15.2015.343 DO - https://doi.org/10.2991/icadme-15.2015.343 ID - Wang2015/10 ER -