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Combination of optimization techniques and simulation techniques is found to be useful and efficient in simulating healthcare systems [ 31– 31].
Additionally, a model based on fluid dynamic simulation techniques is proposed.
One of the major limitations of simulation techniques is its inability to guarantee optimality of the developed solution.
The design of engineering systems under probabilistic model uncertainty using stochastic simulation techniques is discussed in this paper.
A method combining these two purposes at a time and intended to obtain a drastic reduction of the computational labor implied by simulation techniques is proposed.
The determination of periodic states of cyclic chemical processes by standard simulation techniques is computationally inefficient due to the long transient phase.
Similar(48)
Stochastic simulation techniques are implemented in order to simulate samples of these variables that lead to system failure.
New analytical and simulation techniques are described in this paper.
For the numerical investigations, three different simulation techniques are applied.
Unfortunately the testing and simulation techniques are lacking of in verifying the correctness of the systems.
For such systems, analytical techniques have limited applicability, and efficient simulation techniques are, therefore, required.
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