Math Modeling Research Paper
12/14/2020
Problem Basics
Summary (Abstract)
Breaking Down the Summary (Abstract)
Restate the Problem�“We were tasked with…”
Briefly Describe the Methods Used
“We created a method to…”
“After implementing this method, we found…”
“We analyzed…”
Describe Final Results Briefly and Conclusion
“Our final solution…”
“We determined…”
Formal Introduction
Assumptions & Justifications
Example #1
“The number of consumers in each state is proportional to the state’s total population.”
“Although different states may be more inclined to buy the
company’s recreational equipment, for the sake of the metric and
measuring taxes we assume that the state’s population correlates
with the number of consumers from that state to simplify calculations.”
Assumption
Justification
Collecting data on consumers in each state would be too time consuming + not add much to the model.
Example #2
“The shipping occurs on Monday, November 14, 2016, which is used on the UPS website to find one-day shipping area.”
“We wish to model the situation that occurs most of the time, which
is not during “rush season,” or between Black Friday and
Christmas. Shipping also only occurs during business days, so
sending a package on Friday would be received by Monday. We
chose November 14, 2016, as it is not during “rush season” and is
a Monday, so it is uninterrupted by non-business days.”
Assumption
Justification
This assumption reduces complexity by using data from average cases.
Actual Math + Data
The model + what it does
Data used to create/test the model
Process + calculations done to create the model + solution
★
★
★
Explaining process + why they set up the model in a certain way.
Data + Calculations
After finding the mean ZIP code, we allowed a ± 20% range (Table 1), which allowed for freedom in states that are oddly shaped, have inconsistent labelling patterns or have few major roadways, and used the ZIP code within that range that was closest to an interstate or highway.
Data + Calculations
The closer a ZIP code is to the median amount, the more preferable it was. It was most optimal to find a location near an intersection of highways and interstates. We tested all possible ZIP codes by putting them into the UPS website [1] and compared them to determine which covered the most area.
Justification
What to do?
Example
Example
Strengths and Weaknesses
List and explain
Most important —> least important
What makes this model accurate/realistic?
Inaccurate/unrealistic?
Specific &
reason
How final > initial
Walks through reasoning: why is this beneficial?
Explains why another approach could have been better
Sensitivity Analysis
What to put?
Conclusion and Final Recc, Future Work
Conclude by explaining your solution and how it answers the problem:
P1: what you determined for 1) min # warehouses 2) where warehouses should be located:
“We determined the minimum number and optimal placement of warehouses depending on their ZIP codes and their proximity to major roadways. The minimum number of warehouses added that would allow the 48 states to receive one-day shipping is 25. The optimal placement of warehouses can be seen in Figure 5… ”
P2: 1) how locations affect customers’ tax liability and 2) any changes/modifications
Conclusion and Final Recc, Future Work
P3/4: implementation and recommendation:
“In reality, the warehouses will have to be built one at a time. While the new warehouses could be built east to west, gradually expanding our customer base,
there is a better way.
We propose that the company build new warehouses in the following four cities: Denver, Colorado; Marion, Arkansas; Fresno, California; and Janesville, Wisconsin. Building these four bases ensures that a majority of the United States will have access to two-day shipping from the company. This will allow for a massively increased income for the company, which will allow for faster expansion as they continue to build the 21 remaining warehouses to ensure one-day shipping nationwide.”
Future work: what else requires further study?
Attendance Form
https://tinyurl.com/ghmm1214