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Simulation with Arena

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Simulation with Arena
Assignment G2: a multi-echelon inventory policy
Christopoulou Evdoxia Kuodzevicius Bernardas 101283 534893

10/12/2012

Preliminaries
The given Arena model is a steady-state model, because there is no clear event that could indicate the end of model run and actually we are interested in the long run behavior of the system represented by the given model. Before we start to do the main parts of the assignment, that is design of experiments and optimization, we conduct some preliminary experiments to check if the model could be modified in order to get better results. First we set the number of replications to 30 and we choose the length of each replication be 730 days (two years), which we think should be enough to reach the steady-state. When we run the model with these settings, we get that the mean of the main response variable - average cost - is 568.4 and the half width is equal to 2.37. Although the confidence interval is not extremely wide taking into account the relatively high value of mean, we still perform a check whether it is possible to get more precise results by using common random numbers. To figure out if the model would benefit from the use of CRN we perform a pilot study. In this study we need to have two different scenarios and then we can decide whether it is useful to use CRN by checking the following inequality: { } { } { }

and if this inequality holds, then it is worth using CRN in the model. In our case the scenarios differ in three variables: review period , the lead time and . For the first scenario we use the values of the base case, that is and . For the second scenario we change these values to and . We select as the response variable the average cost, for which we will check whether the inequality holds. So in the formula { } is the variance of the average cost in scenario . To calculate this variance we above

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