Many practical design problems are multidisciplinary and typically involve the transfer of complex information between analysis modules. In solving such problems, the method for performing multidisciplinary analyses greatly affects the speed of the total design time. Thus, it is very important to group and order a multidisciplinary analysis (MDA) process so as to minimize the total computational time and cost by decomposing a large multidisciplinary problem into several subsystems and then processing them in parallel. This study proposes a decomposition method that exploits parallel computing, including the determination of an optimal number of subsystems by using a multi-objective optimization formulation and a messy genetic algorithm (GA) modified to handle discrete design variables. In the suggested method, an MDA process is decomposed and sequenced for simultaneously minimizing the feedback couplings within each subsystem, the total couplings between subsystems, the variation of computation times among subsystems, and the computation time of each subsystem. The proposed method is applied to the decomposition of an artificial complex system example and a multidisciplinary design problem of a rotorcraft with 17 analysis modules; promising results are presented using this proposed method.

References

References
1.
Azarm
,
S.
, and
Li
,
W.-C.
,
1988
, “
A Two-Level Decomposition Method for Design Optimization
,”
Eng. Optim.
,
13
(
3
), pp.
211
224
.10.1080/03052158808940956
2.
Rogers
,
J. L.
,
1989
, “
DeMAID—A Design Manager's Aid for Intelligent Decomposition User's Guide
,”
NASA Technical Memorandum (101575)
.
3.
Kusiak
,
A.
, and
Larson
,
N.
,
1995
, “
Decomposition and Representation Methods in Mechanical Design
,”
Trans. ASME J. Mech. Des.
,
117
(
B
), pp.
17
24
.10.1115/1.2836453
4.
Michelena
,
N. F.
, and
Papalambros
,
P. Y.
,
1995
, “
Optimal Model-Based Decomposition of Powertrain System Design
,”
Trans. ASME J. Mech. Des.
,
117
(
4
), pp.
499
505
.10.1115/1.2826710
5.
Altus
,
S. S.
,
Kroo
,
I. M.
, and
Gage
,
P. J.
,
1996
, “
A Genetic Algorithm for Scheduling and Decomposition of Multidisciplinary Design Problems
,”
Trans. ASME J. Mech. Des.
,
118
(
4
), pp.
486
489
.10.1115/1.2826916
6.
English
,
K.
,
Bloebaum
,
C. L.
, and
Miller
,
E.
,
2001
, “
Development of Multiple Cycle Coupling Suspension in the Optimization of Complex Systems
,”
Struct. Multidiscip. Optim.
,
22
(
4
), pp.
268
283
.10.1007/PL00013284
7.
Park
,
H. W.
,
Kim
,
M. S.
, and
Choi
,
D. H.
,
2002
, “
A New Decomposition Method for Parallel Processing Multi-Level Optimization
,”
KSME Int. J.
,
16
(
5
), pp.
609
618
.10.1007/BF03184810
8.
Allison
,
J. T.
,
Kokkolaras
,
M.
, and
Papalambros
,
P. Y.
,
2009
, “
Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization
,”
Trans. ASME J. Mech. Des.
,
131
(
8
), p.
0810081
.10.1115/1.3178729
9.
Shan
,
S. Q.
, and
Wang
,
G. G.
,
2010
, “
Survey of Modeling and Optimization Strategies to Solve High-Dimensional Design Problems With Computationally-Expensive Black-Box Functions
,”
Struct. Multidiscip. Optim.
,
41
(
2
), pp.
219
241
.10.1007/s00158-009-0420-2
10.
Li
,
S.
,
2009
, “
Matrix-Based Decomposition Algorithms for Engineering Applications: The Survey And Generic Framework
,”
Int. J. Prod. Dev.
,
9
(
1-3
), pp.
78
110
.10.1504/IJPD.2009.026175
11.
Steward
,
D.
,
1981
,
Systems Analysis and Management: Structure, Strategy, and Design
,
Petrocelli Books
,
New York, NY
.
12.
Browning
,
T. R.
,
2001
, “
Applying the Design Structure Matrix to System Decomposition and Integration Problems: A Review and New Directions
,”
IEEE Trans. Eng. Manage.
,
48
(
3
), pp.
292
306
.10.1109/17.946528
13.
Yassine
,
A.
, and
Braha
,
D.
,
2003
, “
Complex Concurrent Engineering and the Design Structure Matrix Method
,”
Concurr. Eng. Res. Appl.
,
11
(
3
), pp.
165
176
.10.1177/106329303034503
14.
Chen
,
L.
,
Ding
,
Z.
, and
Li
,
S.
,
2005
, “
A Formal Two-Phase Method for Decomposition of Complex Design Problems
,”
Trans. ASME J. Mech. Des.
,
127
(
2
), pp.
184
195
.10.1115/1.1778186
15.
Rogers
,
J. L.
,
1997
, “
Reducing Design Cycle Time and Cost Through Process Resequencing
,”
International Conference on Engineering Design, Tampere
.
16.
Krishnamachari
,
R. S.
, and
Papalambros
,
P. Y.
,
1997
, “
Hierarchical Decomposition Synthesis in Optimal Systems Design
,”
Trans. ASME J. Mech. Des.
,
119
(
4
), pp.
448
455
.10.1115/1.2826389
17.
Chen
,
D. Z.
, and
Liu
,
C. P.
,
1999
, “
A Hierarchical Decomposition Scheme for the Topological Synthesis of Articulated Gear Mechanisms
,”
Trans. ASME J. Mech. Des.
,
121
(
2
), pp.
256
263
.10.1115/1.2829452
18.
Sobieszczanski-Sobieski
,
J.
, and
Haftka
,
R. T.
,
1997
, “
Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments
,”
Struct. Multidiscip. Optim.
,
14
(
1
), pp.
1
23
.10.1007/BF01197554
19.
Cramer
,
E. J.
,
Dennis
,
J. J. E.
,
Frank
,
P. D.
,
Lewis
,
R. M.
, and
Shubin
,
G. R.
,
1994
, “
Problem Formulation for Multidisciplinary Optimization
,”
SIAM J. Optim.
,
4
(
4
), pp.
754
776
.10.1137/0804044
20.
Braun
,
R. D.
,
1996
, “
Collaborative Optimization: An Architecture for Large-Scale Distributed Design
,”
Ph.D. thesis
,
Stanford University
,
Stanford, CA
.
21.
Sobieszczanski-Sobieski
,
J.
,
Agte
,
J. S.
, and
Sandusky
, Jr.,
R. R.
,
2000
, “
Bilevel Integrated System Synthesis
,”
AIAA J.
,
38
(
1
), pp.
164
172
.10.2514/2.937
22.
Kodiyalam
,
S.
, and
Sobieszczanski-Sobieski
,
J.
,
2000
, “
Bilevel Integrated System Synthesis With Response Surfaces
,”
AIAA J.
,
38
(
8
), pp.
1479
1485
.10.2514/2.1126
23.
Sobieszczanski-Sobieski
,
J.
, and
Kodiyalam
,
S.
,
2001
, “
BLISS/S: A New Method for Two-Level Structural Optimization
,”
Struct. Multidiscip. Optim.
,
21
(
1
), pp.
1
13
.10.1007/s001580050163
24.
Sobieszczanski-Sobieski
,
J.
,
Altus
,
T. D.
,
Phillips
,
M.
, and
Sandusky
,
R.
,
2003
, “
Bilevel Integrated System Synthesis for Concurrent and Distributed Processing
,”
AIAA J.
,
41
(
10
), pp.
1996
2003
.10.2514/2.1889
25.
Kim
,
H. M.
,
Rideout
,
D. G.
,
Papalambros
,
P. Y.
, and
Stein
,
J. L.
,
2003
, “
Analytical Target Cascading in Automotive Vehicle Design
,”
Trans. ASME J. Mech. Des.
,
125
(
3
), pp.
481
489
.10.1115/1.1586308
26.
Park
,
H. W.
,
Lee
,
S. J.
,
Lee
,
H. S.
, and
Choi
,
D. H.
,
2004
, “
Adaptive Parallel Decomposition for Multidisciplinary Design
,”
KSME Int. J.
,
18
(
5
), pp.
814
819
.
27.
Rogers
,
J. L.
,
1996
, “
DeMAID/GA User's Guide Design Manager's Aid for Intelligent Decomposition With a Genetic Algorithm
,”
NASA Technical Memorandum (110241)
.
28.
Goldberg
,
D.
,
Deb
,
K.
, and
Korb
,
B.
,
1989
, “
Messy Genetic Algorithms: Motivation, Analysis, and First Results
,”
Complex Syst.
3
(
5
), pp.
493
530
.
29.
Kim
,
I. Y.
, and
de Weck
,
O. L.
,
2005
, “
Variable Chromosome Length Genetic Algorithm for Progressive Refinement in Topology Optimization
,”
Struct. Multidiscip. Optim.
,
29
, pp.
445
456
.10.1007/s00158-004-0498-5
30.
Brie
,
A. H.
, and
Morignot
,
P.
,
2005
, “
Genetic Planning Using Variable Length Chromosomes
,”
Proceedings of the 15th International Conference on Automated Planning and Scheduling
,
AAAI Press
,
Monterey, CA
.
31.
Eppinger
,
S. D.
,
Whitney
,
D. E.
, and
Gebala
,
D. A.
,
1992
, “
Organizing the Tasks in Complex Design Projects: Development of Tools to Represent Design Procedures
,”
NSF Design and Manufacturing Systems Conference
,
Atlanta, Georgia
.
32.
Miettinen
,
K.
,
1999
,
Nonlinear Multiobjective Optimization
,
Kluwer Academic Publishers
,
Boston, MA
.
33.
Bäck
,
T.
,
1996
,
Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms
,
Oxford University Press
,
New York, NY
.
34.
Gen
,
M.
, and
Cheng
,
R.
,
1997
,
Genetic Algorithms and Engineering Design
,
Wiley
,
New York, NY
.
You do not currently have access to this content.