Saturday, May 17
Today we visited Animal Kingdom, arriving at the park just at before it opened. We opened with Expedition Everest, then went to Expedition Everest, then tried Expedition Everest again. Needless to say, definitely a good intro to the day. After a wakeup call from the yeti, we migrated over to the Safari where we saw some of the multitude of animals Disney maintains at the park, including hippos, rhinos, giraffes, crocodiles (Stella's favorite), and some lively flamingos, all of which were 100% real.
We then went to see Finding Nemo the Musical, a fantastic retelling of the movie considering it was only an hourlong show, then split up in the park for the rest if the day until three. My group ended up riding Dinosaur then Kali River Rapids, both of which were a lot of fun despite the long wait time at the river rapids. Lessons learned from the day trip included that flamingos turn pink from the shrimp they eat, black rhino's horns are made out of keratin like our finger nails, elephants' pregnancies last up to 23 months, and that deforestation is a major cause of flash flooding.
After we all had a chance to catch a quick nap and freshen up, we met in the professors' room for a continuation on the lectures started on Thursday. We were first introduced to the Knapsack problem, a complex problem that very much relates to what we've been talking about with Graphs. Here is an example of the knapsack problem. Imagine you are packing for a long trip, say six months, but you are flying. The airline you are using will only allow 2 bags. You have to look at the weight and size of each item and decide which items you will bring. It might sound pretty easy, but coming up with an algorithm to achieve this task has yet to be done.
Dr. Hutson expanded upon his lecture on Linear programming by showing us the beginning basics of how to solve these problems. He did a really good job of wrapping up a few courses in vectors, matrices, and operations research in half a day! It was really interesting to see a computational way to see how to get the answers that the computer generates for you. These answers that he showed us gave very precise solutions which can be good, but not always the ideal answer. For example, if you were looking to get a precise answer on how many of those items you could fit in your bag, you wouldn't want the answer to be 12.243. It would have to be an integer solution. This is where things got a little more technical. This, however, was really cool for a lot of students because we now got to see application of concepts we learned about in previous math classes. For example, in MTH-160, we learned about null spaces and today we learned how those can apply to solve solutions to our linear programming problems. This transitioned very nicely into continuing Dr. Harris' lecture where we began to take an in-depth look at the very famous Traveling Salesman Problem.
This problem is really the focus of our studies right now. The traveling salesman problem (TSP) asks the following question: given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the original city? We applied this problem to Epcot yesterday when we competed to go to the maximum number of rides in the shortest amount of time. Today we learned some algorithms to help assist solving TSP, but ultimately we discovered there is no algorithm to solve this problem.
Tomorrow looks like we'll finally get a little rest from all the parks.
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