TY - GEN
T1 - A distributed coevolutionary multidisciplinary design optimization algorithm
AU - Xing, Yonggang
AU - Tang, Shuo
PY - 2010
Y1 - 2010
N2 - In order to provide efficient algorithm for multidisciplinary design optimization of complex coupled systems, a distributed coevolutionary multidisciplinary design optimization algorithm is proposed. The algorithm imitates the biological competitive and cooperative coevolutionary process in ecological systems. The ideas of decomposition and cooperation in coevolutionary algorithm combine with the ideas of decomposition and synergism in MDO. Based on the method of domain decomposition and the implicit iteration strategy, the complex coupled system is decomposed into relatively independent and autonomic multidisciplinary systems. Each discipline is modeled as a species. Thus the competitivecooperative adaptive coevolutionary multidisciplinary optimization process has been modeled amongst the populations of multidisciplinary species. For illustrating the proposed algorithm, a multidisciplinary design optimization test problem generated by a robust simulator called CASCADE is utilized to simulate. Experimental results reveal the proposed algorithm has good search capability and convergence performance. Hence, the presented algorithm is efficient and robust in solving multidisciplinary design optimization problem of complex coupled systems.
AB - In order to provide efficient algorithm for multidisciplinary design optimization of complex coupled systems, a distributed coevolutionary multidisciplinary design optimization algorithm is proposed. The algorithm imitates the biological competitive and cooperative coevolutionary process in ecological systems. The ideas of decomposition and cooperation in coevolutionary algorithm combine with the ideas of decomposition and synergism in MDO. Based on the method of domain decomposition and the implicit iteration strategy, the complex coupled system is decomposed into relatively independent and autonomic multidisciplinary systems. Each discipline is modeled as a species. Thus the competitivecooperative adaptive coevolutionary multidisciplinary optimization process has been modeled amongst the populations of multidisciplinary species. For illustrating the proposed algorithm, a multidisciplinary design optimization test problem generated by a robust simulator called CASCADE is utilized to simulate. Experimental results reveal the proposed algorithm has good search capability and convergence performance. Hence, the presented algorithm is efficient and robust in solving multidisciplinary design optimization problem of complex coupled systems.
KW - Competetivecooperative
KW - Complex coupled systems
KW - Distributed coevolutionary algorithm
KW - Multidisciplinary design optimization
UR - http://www.scopus.com/inward/record.url?scp=77956424208&partnerID=8YFLogxK
U2 - 10.1109/CSO.2010.16
DO - 10.1109/CSO.2010.16
M3 - 会议稿件
AN - SCOPUS:77956424208
SN - 9780769540306
T3 - 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
SP - 77
EP - 80
BT - 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010
T2 - 3rd International Joint Conference on Computational Sciences and Optimization, CSO 2010: Theoretical Development and Engineering Practice
Y2 - 28 May 2010 through 31 May 2010
ER -