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Mat 540 Problem Solving Paper

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Step 2: Generate a random number between 0 and 1 by using the random number generator in the programming software and then denoted as r.\\

Step 3: Make the generated random number r connected with the cumulative distribution function (CDF) for every parameter to get a set of deterministic values for parameters in $a_{ij}$, $b_{ij}$ and $c_{ij}$.\\

Following in Figure 3.3 is an example showing how to set a random value for a parameter.\\

Step 4: Replace the interval parameters $a_{ij}$, $b_{ij}$ and $c_{ij}$ by using the set of deterministic values we get from above. And create a classic deterministic linear programming model. \\

Step 5: Sovle the classic deterministic linear programming model in software and generate a set of corresponding deterministic solutions. \\

Step 6: Run the process above plentiful times by repeating the step 2, 3, 4 and 5 in order to obtain the distribution of the solution for each specific decision variable.\\ …show more content…
Meanwhile, the Monte Carlo simulation requires large numbers of computational works of random or pseudo random numbers. With the purpose of getting the distribution for a specific solution, thousands or even millions of times of simulations have to be conducted. Therefore, it would become unrealistic for sovling the intricate practical problems along with a large number of uncertain parameters and variables in the real

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