TY - GEN
T1 - A new integration technique for hierarchically decomposed multi-objective optimization
AU - Wang, Ting Ting
AU - Chen, Xiao Kai
AU - Lin, Yi
PY - 2011
Y1 - 2011
N2 - Multidisciplinary design optimization (MDO) is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. Because of the complex design space of the large-scale system MDO design problem and the serious conflicts between the different design objectives, there is the necessary to seek an objective, flexible, effective way to make multi-objective decision on MDO problem. In this paper, we describe the integration of Advanced Physical Programming within Analytical Target Cascading framework to enable designers to formulate multiple system-level objectives in terms of physically meaningful parameters. The proposed formulation with the general integration of Advanced Physical Programming and Analytical Target Cascading is used to handle with the multi-objective tradeoff problem in different levels. A mathematical example using MDO method demonstrates the proposed framework.
AB - Multidisciplinary design optimization (MDO) is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. Because of the complex design space of the large-scale system MDO design problem and the serious conflicts between the different design objectives, there is the necessary to seek an objective, flexible, effective way to make multi-objective decision on MDO problem. In this paper, we describe the integration of Advanced Physical Programming within Analytical Target Cascading framework to enable designers to formulate multiple system-level objectives in terms of physically meaningful parameters. The proposed formulation with the general integration of Advanced Physical Programming and Analytical Target Cascading is used to handle with the multi-objective tradeoff problem in different levels. A mathematical example using MDO method demonstrates the proposed framework.
KW - Advanced physical programming
KW - Analytical target cascading
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=80053262798&partnerID=8YFLogxK
U2 - 10.1109/AIMSEC.2011.6010097
DO - 10.1109/AIMSEC.2011.6010097
M3 - Conference contribution
AN - SCOPUS:80053262798
SN - 9781457705366
T3 - 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings
SP - 3658
EP - 3661
BT - 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings
T2 - 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011
Y2 - 8 August 2011 through 10 August 2011
ER -