Abstract
Engineering optimization problems often encounter mixed discrete design variables. Very few of the existing methods can obtain a globally optimal solution if the objective functions are non-convex and non-differentiable. In this research, a mixed discrete synthetic approach (MDSA), taking the advantages of random search methods and deterministic search methods, is proposed. Specifically, the modified complex algorithm is combined with the hybrid negative sub-gradient search, coupled with an implicit enumeration checking-point technique, for the solution of mixed-discrete optimization problems. The MDSA is used for the optimal designs of a pressure vessel and a welded beam. The numerical results demonstrate the high reliability and effectiveness of the MDSA as an advanced global method in solving mixed-discrete engineering optimization problems.
| Original language | English (US) |
|---|---|
| Title of host publication | Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference |
| Pages | 414-421 |
| Number of pages | 8 |
| Volume | 1 |
| State | Published - 2003 |
| Event | 44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference - Norfolk, VA, United States Duration: Apr 7 2003 → Apr 10 2003 |
Other
| Other | 44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference |
|---|---|
| Country | United States |
| City | Norfolk, VA |
| Period | 4/7/03 → 4/10/03 |
Fingerprint
ASJC Scopus subject areas
- Architecture
Cite this
Mixed discrete synthetic approach for nonlinear design optimization. / Xiong, Ying; Rao, Singiresu S.
Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Vol. 1 2003. p. 414-421.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Mixed discrete synthetic approach for nonlinear design optimization
AU - Xiong, Ying
AU - Rao, Singiresu S
PY - 2003
Y1 - 2003
N2 - Engineering optimization problems often encounter mixed discrete design variables. Very few of the existing methods can obtain a globally optimal solution if the objective functions are non-convex and non-differentiable. In this research, a mixed discrete synthetic approach (MDSA), taking the advantages of random search methods and deterministic search methods, is proposed. Specifically, the modified complex algorithm is combined with the hybrid negative sub-gradient search, coupled with an implicit enumeration checking-point technique, for the solution of mixed-discrete optimization problems. The MDSA is used for the optimal designs of a pressure vessel and a welded beam. The numerical results demonstrate the high reliability and effectiveness of the MDSA as an advanced global method in solving mixed-discrete engineering optimization problems.
AB - Engineering optimization problems often encounter mixed discrete design variables. Very few of the existing methods can obtain a globally optimal solution if the objective functions are non-convex and non-differentiable. In this research, a mixed discrete synthetic approach (MDSA), taking the advantages of random search methods and deterministic search methods, is proposed. Specifically, the modified complex algorithm is combined with the hybrid negative sub-gradient search, coupled with an implicit enumeration checking-point technique, for the solution of mixed-discrete optimization problems. The MDSA is used for the optimal designs of a pressure vessel and a welded beam. The numerical results demonstrate the high reliability and effectiveness of the MDSA as an advanced global method in solving mixed-discrete engineering optimization problems.
UR - http://www.scopus.com/inward/record.url?scp=0042513818&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0042513818&partnerID=8YFLogxK
M3 - Conference contribution
VL - 1
SP - 414
EP - 421
BT - Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
ER -