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In: Statistics and Probability

A medium-sized airport has a limited number of international flights that arrive and require immigration and...

A medium-sized airport has a limited number of international flights that arrive and require immigration and customs. The airport would like to examine the customs staffing and establish a policy on the number of passengers who should have bags searched and the staffing of the customs facility. The number of passengers who arrive on these large planes is uniformly distributed between 240 and 350, and the simulation is to run until all passengers on the plane have been completely processed (i.e., the number of passengers on the plane determines the replication length). Arriving passengers must first pass through immigration (immigration is outside the boundaries of this model). They then claim their bags and proceed to customs. The interarrival times to customs are distributed as EXPO(0.2), with the first passenger arriving at (or just barely after) time zero; all times are in minutes. The current plan is to have two customs agents dedicated to passengers who will not have their bags searched, with service times distributed as EXPO(0.56). A new airport systems analyst has developed a probabilistic method to decide which customers will have their bags searched. The decision is made when the passengers are about to enter the normal customs queue. The decision process is as follows: a number is first generated from a Poisson distribution with a mean of 7.0. This number is increased by 1, to avoid getting a zero, and a count is started. When the count reaches the generated number, that unlucky passenger is sent to a second line to have his or her bags searched. A new search number is generated and the process starts over. A single agent is dedicated to these passengers, with service times distributed as EXPO(3). Develop a simulation of the proposed system and make 20 replications (i.e., process 20 planes, since a replication ends when the last customer from a plane clears customs), observing statistics on the system time by passenger type (searched vs. not searched), the number of passengers, and agent utilizations.

We are using Arena sim model. How I solve it?

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orchestra answered 1 year ago
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