2016 HiMCM A题特等奖学生论文下载7054
2016 HiMCM A题特等奖学生论文下载7054
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论文摘要如下：
Summary
On your mark, get set, go! Triathlons are globally held competitions that put the fittest of the fit to the test. A local town wants to hold a triathlon and is expecting 2000 athletes – both amateurs and professionals – to participate. The sponsor of the triathlon, Super Tread Racing Company, would like to reduce congestion on the course, and the Town Mayor does not want the public roads to be closed (during the running and cycling segments) for more
than 5.5 hours. In order fulfill both requests, we created divisions that will be used in the race as well as a schedule of wave start times. Furthermore, to determine the advantages that might be achieved by varying the distances of each segment of the triathlon, we developed an agent-based model capable of organizing each segment.
Our agent-based model was created in NetLogo, using data taken from a previous triathlon to determine the apportionment of athlete sex and segment times. We placed the athletes into eight divisions (four per each sex), where each division represents a respective quartile of the course completion times. Congestion was defined as being linearly related to the number of people athletes had to pass and logarithmically related to the number of people around each athlete. We developed the course of the triathlon, in which we demarcated the path into three lanes – fast, main, and slow – where each lane is based on segment times for each athlete. The three-lane system decreases congestion by 72% relative to a base model with no lanes. Separately closing the cycling roads and the running roads allowed us to minimize congestion by 29%. We then used our agent-based model to generate a schedule of wave start times that will fit the criteria set by the CEO and the mayor. We constructed “wave-packets” to further minimize the congestion and road closure time. Each wave-packet contains 55 athletes with a distribution of: 25% fast athletes, 25% slow athletes, and 50% medium-speed athletes. By releasing the wave-packets in order of decreasing average speed, we ensure that wave-packets do not interfere with each other, decreasing congestion by 27%. By testing our model with various values for the separation time between wave-packets, we found that separating wave-packets by 4 minutes would minimize congestion while keeping the road closure time under 5.5 hours.
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