Difference between revisions of "The Line of Least Resistance"

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== Challenges ==
 
== Challenges ==
  
* Creating realistic simulations that take into account most to all variables
+
* Making sure the simulations are realistic for an array of systems by taking into account myriad variables (e.g. understanding the challenges that come with a large system that may not be present with a smaller system, and vice versa)
* Extrapolating the method for creating a better system at the arch into something that can be used to minimize delay time anywhere
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* Learning simulation software
* Coding the app
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* Learning how to code an app
  
 
== Budget ==
 
== Budget ==

Revision as of 18:28, 24 September 2016

Project Overview

On a warm Saturday afternoon, Andrew found himself still waiting 30 minutes after his scheduled trip up the iconic St. Louis arch. Reflecting on the experience weeks later with fellow Systems Science and Engineering student Devon, they hypothesized there had to be a more efficient way to run the system by fixing how they manage the masses with their queues.

We aim to model the current system at the Arch, and then work on designing a system that both accurately models customer behavior and eliminates delay time. Once this has been done, we will develop an application that Arch officials, as well as officials at other tourist attractions, can use to provide suggestions on setting up their queues on a given day in order to minimize delay time while also maximizing profits.

Team Members

  • Devon Essick
  • Andrew Sweren
  • Kjartan Brownell (TA)

Objectives

Note: Each objective depends on the success of the previous one and proximity to the demo.

  • Create a "consulting" application that accurately suggests how to most efficiently (in terms of minimal delay time) set up queues on a given day at a tourist attraction
  • Expand the application in order to be useful to other companies that aim to minimize delay time (not just tourist attractions).
  • Expand application to be able to solve problems other than minimizing delay time (e. g. minimizing wait time).
  • Expand the application to take into account different methods of payment when determining how to maximize profits.

Challenges

  • Making sure the simulations are realistic for an array of systems by taking into account myriad variables (e.g. understanding the challenges that come with a large system that may not be present with a smaller system, and vice versa)
  • Learning simulation software
  • Learning how to code an app

Budget

  • Monitor and peripherals for demo (available from Urbauer 015) - $0
  • Coding software (provided by school) - $0

Total: $0

Gantt Chart

EssickGantt.png

Design and Solutions

Results