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Research Papers

Generalized Coupling Management in Complex Engineering Systems Optimization

[+] Author and Article Information
Sulaiman F. Alyaqout

Mechanical Engineering Department,  Kuwait University, Safat, Kuwaits.alyaqout@ku.edu.kw

Diane L. Peters1

 University of Michigan, 2250 G. G. Brown Building, 2350 Hayward Street, Ann Arbor, MI 48109dlpeters@umich.edu

Panos Y. Papalambros

A. Galip Ulsoy

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109-2125ulsoy@umich.edu

1

Corresponding author.

J. Mech. Des 133(9), 091005 (Sep 09, 2011) (10 pages) doi:10.1115/1.4004541 History: Received September 27, 2010; Revised June 22, 2011; Published September 09, 2011; Online September 09, 2011

Decomposition-based design optimization strategies are used to solve complex engineering system problems that might be otherwise unsolvable. Yet, the associated computational cost can be prohibitively high due to the often large number of iterations needed for coordination of subproblem solutions. To reduce this cost one may exploit the fact that some systems may be weakly coupled and their interactions can be suspended with little loss in solution accuracy. Suspending such interactions is usually based on the analyst’s experience or experimental observation. This article introduces an explicit measure of coupling strength among interconnected subproblems in a decomposed system optimization problem, along with a systematic way for calculating it. The strength measure is then used to suspend weak couplings and, thus, improve system solution strategies such as the model coordination method. Examples show that the resulting strategy may decrease the number of required function evaluations significantly.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 1

Nonhierarchical system interactions notation

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Figure 2

The model coordination method

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Figure 3

The model coordination method written in the coupled systems optimization framework

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Figure 4

The model coordination method with variable x 1 suspended

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Figure 5

The HCS algorithm flowchart

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Figure 6

The model coordination method for the unconstrained optimization example

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Figure 7

System iterations with and without suspension

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Figure 8

Optimization coupling function behavior without suspension

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Figure 9

Structural example configuration

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Figure 10

Comparison of coupling strength in structural example

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Figure 11

Comparison of coupling strength in DC motor example

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