Part 1. The Bavarian Motor Company (BMC) manufactures expensive luxury cars in Hamburg, Germany, and exports cars to sell in the United States. The exported cars are shipped from Hamburg to ports in Newark, New Jersey and Jacksonville, Florida. From these ports, the cars are transported by rail or truck to distributors located in Boston, Massachusetts; Columbus, Ohio; Atlanta, Georgia; Richmond, Virginia; and Mobile, Alabama. The below figure shows the possible shipping routes available to the company along with the transportation cost for shipping each car along the indicated path. Currently, 200 cars are available at the port in Newark and 300 are available in Jacksonville. The numbers of cars needed by the distributors in Boston, Columbus, Atlanta, Richmond, and Mobile are 100, 60, 170, 80, and 70, respectively. BMC wants to determine the least costly way of transporting cars from the ports in Newark and Jacksonville to the cities where they are needed. Formulate the LP and solve it using software of your choice. Conduct sensitivity analysis by varying the cost of shipping across selected links. Interpret the results. +100 Boston $30 Newark $50 -200 1 Columbus 3 +60 $40 $40 $35 Richmond +80 $30 Atlanta +170 $25 $45 $50 $35 Mobile J'ville 7 +70 |-300 $50 Describe how you would go about solving an actual vehicle distribution problem across the domestic United States with multiple seaports of entry and more than 300 distributors to cover all cities with a population of at least 100 thousand residents. What software would you use? How would you manage the data? What would be your approach to employing sensitivity analysis in a problem of this scale? (To guide your thinking about this problem, you could start with a list of cities and their locations by latitude and longitude as shown in https://en.wikipedia.org/wiki/List of United States cities by_population. e Imagine that transportation cost is proportional to the distance between each pair of cities and demand, cars needed, is proportional to population.)
Part 1. The Bavarian Motor Company (BMC) manufactures expensive luxury cars in Hamburg, Germany, and exports cars to sell in the United States. The exported cars are shipped from Hamburg to ports in Newark, New Jersey and Jacksonville, Florida. From these ports, the cars are transported by rail or truck to distributors located in Boston, Massachusetts; Columbus, Ohio; Atlanta, Georgia; Richmond, Virginia; and Mobile, Alabama. The below figure shows the possible shipping routes available to the company along with the transportation cost for shipping each car along the indicated path. Currently, 200 cars are available at the port in Newark and 300 are available in Jacksonville. The numbers of cars needed by the distributors in Boston, Columbus, Atlanta, Richmond, and Mobile are 100, 60, 170, 80, and 70, respectively. BMC wants to determine the least costly way of transporting cars from the ports in Newark and Jacksonville to the cities where they are needed. Formulate the LP and solve it using software of your choice. Conduct sensitivity analysis by varying the cost of shipping across selected links. Interpret the results. +100 Boston $30 Newark $50 -200 1 Columbus 3 +60 $40 $40 $35 Richmond +80 $30 Atlanta +170 $25 $45 $50 $35 Mobile J'ville 7 +70 |-300 $50 Describe how you would go about solving an actual vehicle distribution problem across the domestic United States with multiple seaports of entry and more than 300 distributors to cover all cities with a population of at least 100 thousand residents. What software would you use? How would you manage the data? What would be your approach to employing sensitivity analysis in a problem of this scale? (To guide your thinking about this problem, you could start with a list of cities and their locations by latitude and longitude as shown in https://en.wikipedia.org/wiki/List of United States cities by_population. e Imagine that transportation cost is proportional to the distance between each pair of cities and demand, cars needed, is proportional to population.)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Transcribed Image Text:Part 1. The Bavarian Motor Company (BMC) manufactures expensive luxury cars in Hamburg, Germany, and exports cars to sell in
the United States. The exported cars are shipped from Hamburg to ports in Newark, New Jersey and Jacksonville, Florida. From
these ports, the cars are transported by rail or truck to distributors located in Boston, Massachusetts; Columbus, Ohio; Atlanta,
Georgia; Richmond, Virginia; and Mobile, Alabama. The below figure shows the possible shipping routes available to the company
along with the transportation cost for shipping each car along the indicated path. Currently, 200 cars are available at the port in
Newark and 300 are available in Jacksonville. The numbers of cars needed by the distributors in Boston, Columbus, Atlanta,
Richmond, and Mobile are 100, 60, 170, 80, and 70, respectively. BMC wants to determine the least costly way of transporting cars
from the ports in Newark and Jacksonville to the cities where they are needed. Formulate the LP and solve it using software of
your choice. Conduct sensitivity analysis by varying the cost of shipping across selected links. Interpret the results.
+100
Boston
$30
Newark
$50
-200
1
Columbus
3
+60
$40
$40
$35
Richmond
+80
$30
Atlanta
+170
$25
$45
$50
$35
Mobile
J'ville
7
+70
|-300
$50
Describe how you would go about solving an actual vehicle distribution problem across the domestic United States with multiple
seaports of entry and more than 300 distributors to cover all cities with a population of at least 100 thousand residents. What
software would you use? How would you manage the data? What would be your approach to employing sensitivity analysis in a
problem of this scale? (To guide your thinking about this problem, you could start with a list of cities and their locations by latitude
and longitude as shown in https://en.wikipedia.org/wiki/List of United States cities by_population. e Imagine that
transportation cost is proportional to the distance between each pair of cities and demand, cars needed, is proportional to
population.)
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