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Figure 1. Implementation of the proposed RDO
Implementation of the
RDO Approach
responses as per the DOE in step (i), and iii) finally
checking the convergence to obtain the robust
optimum solution. It can be noted from the flow
chart that during each update of the DVs in the
optimization process the MLSM based response
approximation is re-called and a new approxima-
tion function is formed. However, this is not the
case for the LSM based RSM, where a single ap-
proximation function gets operated throughout the
optimization process. It is worth mentioning here
that the choice of initial solution is an important
issue in metamodel based optimization procedure.
For the conventional LSM based RSM approach,
a poor initial guess not only increases the number
of iterations, but also warns the convergence of
The implementation procedure of the proposed
RDO for linear dynamic system is demonstrated
through a flow chart in Figure 1. The procedure
is basically a three-stage interlinked procedure,
viz.: i) stochastic dynamic analysis of the finite
element model for selected set of input variables
as per the DOE to obtain the required stochastic
responses and subsequently the constraint of the
optimization problem, ii) evaluation of the con-
straint function at the iteration point following
the MLSM based RSM during each iteration of
the optimization process utilizing the computed
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