Our primary objective was to create and analyze a model of Busch Gardens Tampa on SIMUL8 in order to minimize wait time through implementation of a unique and free fastpass system. Our fastpass implementation would collectively lower wait times for each park goer, as seen in the tables of our results section thus satisfying the objective we set out to accomplish.
In regards to the efficacy of our system, in Figure 16 it is clear that more people are waiting less time throughout their day. The blue line corresponds to Model 2 (with fastpasses), the orange line corresponds to Model 1 (without fastpasses). The x-axis of these graphs are time segments of the cumulative time that people spent in a line throughout their day. The y-axis corresponds to the number of people who fell into those wait time segments. So the goal is to have the orange line (Model 1, no fastpass) be greater than the blue line (Model 2, with fastpasses) in the higher x-axis segments. Thus we hope the blue line (Model 2, with fastpasses), is greater than the orange line (Model 1, no fastpass) in the first few x-axis time segments. This means that we have more people waiting less time in the beginning of the day, and fewer people waiting more time near the end of the day, smoothing out the peak wait times in the park. In summary more people are waiting less time, and less people are waiting more time. Our goal was to move clusters of people from segments in high cumulative wait time segments as seen in Figure 18 and move them to the lower wait time segments as seen in Figure 17. Due to the fact that everyone will experience some sort of wait time in their day, our model better distributes people throughout the park thanks to our fastpass system.
Our fastpass system enables us to optimize ride wait times as well. Table 5 shows how we were able to lower the average wait times by 5.52%, 19.91%, and 2.70% for Cheetah Hunt, Montu, and Kumba respectively. Before we implemented our fastpass, as seen in Figure 21, Cheetah Hunt reached its peak wait time by 10:30AM. After implementing the fastpasses, Figure 22 shows that Cheetah Hunt did not reach its peak wait time until 12:20PM. This almost 2 hour discrepancy is a key difference that helps lower people’s cumulative wait times since people are now riding other roller coasters other than Cheetah Hunt first more frequently. This allows these other roller coaster to be busier in the morning since they have capacity that is being underutilized. While SheiKra did have an average wait time increase of 20%, the average wait time of 33 minutes is not outlandish and this helped to reduce the wait times of the other attractions.
*All figures referenced in discussion can be viewed in Results.