This is the solution to a Procurement and Transportation case presented to us by Informs. It consists of high-level details of the solution we presented. We used advanced analytics, use of greedy algorithms, and visualization techniques to analyze the data presented and found out new ways to solve Supply Chain Procurement and Transport problems.
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Case Solution
1. PATHFINDERS
INFORMS OMCC | NOVEMBER 13 – 17 | DALLAS, TX
Mehul Gangwal
MS IT and Management
Kshitija Kulkarni
MS IT and Management
Sahil Ratra
MS Management Science
3. 3WHERE TECHNOLOGY REVEALS PATH
Route Selected – Line Haul Rate
Trailer Type
State Permits
BY ROAD
BY RAIL
Carriage Cost
Transit Cost
Transportation Cost
BY AIR
COST DEPENDENCY
Drayage
Rail Transit
Trailer Type
4. 4WHERE TECHNOLOGY REVEALS PATH
OUR APPROACH
Standardization:
• Z-Scores of distance, weighted graph
• Dijkstra’s Algorithm: Using the shortest path on this data outputs and finding the best path through
these major cities
• Implementation does NOT use a heap - Uses a sorted list: unvisited = [ [distance_to_a, a],
[distance_to_b, b] ]
• O(1)
Further:
• If we get Line Rates for all states, then we’ll use weighted Z-Scores (Ex: 0.8*distance + 0.2*Line Rate)
• Dijkstra’s algorithm: Weighted Z-Scores
Output:
5. 5WHERE TECHNOLOGY REVEALS PATH
5
s
t1
n
n
n
2
18
2
9
14
15
5
30
20
Denver, CO
Albuquerque, NM
Kansas City, KS
Oklahoma City, OK
Little Rock, AR
Dallas, TX
6. 6WHERE TECHNOLOGY REVEALS PATH
45.66% Low Over Width and Over Height
Charges
21%
33.33%
45.66%
Permit Rate
Percentage
-1.366 -0.56 1.03
Z-score
PERMIT DEPENDENCY
8. 8WHERE TECHNOLOGY REVEALS PATH
TRACTOR
Los Angeles, CA
$4570
San Diego, CA
$5684
Newark, NJ
$5966.71
Trailer: T4
9. 9WHERE TECHNOLOGY REVEALS PATH
TRUCK
Seattle, WA
$6139.034
Atlanta, GA
$3684.409
Denver, CO
$2566.807
Trailer: T4
10. WHERE TECHNOLOGY REVEALS PATH 10
I
B
C C C C
B
C
CATERPILLAR C3000 FORKLIFT
Case 1 Case 2
San Antonio San Antonio San Antonio San Antonio San Antonio
Dallas Dallas Dallas Dallas Dallas
2T1 T1 T1 T1 T1
T2 T2 T2 T2 T1
3 4 5 2
14 14 14 14 14
12 11 10 9 12
11. WHERE TECHNOLOGY REVEALS PATH 11
CATERPILLAR C3000 FORKLIFT
Route Road/Rail Forklift
Count
Trailer
Type
Miles FSC Cost
Indianapolis -> Bloomington Road 2 T4 51.1 1.89 96.88
Bloomington -> Carmel Road 12 T4 72.9 1.58 115.47
Carmel -> San Antonio Rail 14 - 1192.5 - 1520.00
San Antonio -> Dallas Road 14 T4 292.3 1.65 484.04
Indianapolis -> Dallas Road and
Rail
14 T4 1608.8 1.70 2216.40
12. WHERE TECHNOLOGY REVEALS PATH 12
Chicago
Aurora
Joliet Joliet Joliet Joliet
Aurora
Joliet
CATERPILLAR C3000 FORKLIFT
Case 1 Case 2
San Antonio San Antonio San Antonio San Antonio San Antonio
Dallas Dallas Dallas Dallas Dallas
2 3 4 5 2
12 11 10 9 12
1414141414
T1 T1 T1 T1 T1
T2 T2 T2 T2 T1
13. WHERE TECHNOLOGY REVEALS PATH 13
CATERPILLAR C3000 FORKLIFT
Route Road/Rail Forklift
Count
Trailer
Type
Miles FSC Cost
Chicago -> Aurora Road 2 T4 41.5 1.58 65.57
Aurora -> Joliet Road 12 T4 35.9 0.99 30.03
Joliet -> San Antonio Rail 14 - 1166.8 - 1612.00
San Antonio -> Dallas Road 14 T4 292.3 1.656 484.04
Chicago -> Dallas Road and
Rail
14 T4 1536.5 1.408 2191.64
14. WHERE TECHNOLOGY REVEALS PATH 14
1 CRATE OF PLASTIC INJECTION MATERIAL
ROAD (USING T2)
Detroit -> Dallas
AIR
Cleveland -> Dallas
Columbus -> Dallas Columbus -> Dallas
Detroit -> Dallas
Cleveland -> Dallas
$2244.53, 3 Days
$2034.24, 3 Days
$2269.44, 3 Days
$4040, 1 Day
$3390, 2 Days
$3340, 3 Days
Using T2 , we saved Over Height costs by 37% at the expense of 15% extra fuel.
37%
15. 15WHERE TECHNOLOGY REVEALS PATH
NOV 18 NOV 19 NOV 20
Hydraulic Excavator
Crawler Tractor
Injection Material
Rock Truck
Forklift
TimeLine
$15,137.81
$ 4570
$ 2566.9
$ 3773
$ 2036.3
$ 2191.64
TIMELINE AND COST
16. WHERE TECHNOLOGY REVEALS PATH 16
CONCLUSION
We found out that Line Haul rate differs for all states
and it has a high weightage in determination of route
LINE HAUL RATES TAKE OVER MILES
01
We found out that these charges are distributed in a
pattern in the US. If we transport via Central US, we
SAVE MONEY.
OVER WIDTH AND OVER HEIGHT CHARGES
02
flexible and scalable approach. An algorithm to
calculate weighted graph using distance. Scalable it to
use Line Rate.
DIJKSTRA’S ALGORITHM
04
We concentrated on cost saving more as the max days
we needed were 3. We deliver on time.
DELIVERY TIME
03
We can only use air transport when it’s very urgent.
TRANSPORT VIA AIR IS WAY TOO COSTLY
05
CUSTOMER
SERVICE
RELIABLE AND
TRUSTWORTHY
17. 17WHERE TECHNOLOGY REVEALS PATH
http://www.supplychainquarterly.com/topics/Logistics/20140
311-the-real-impact-of-high-transportation-costs/
https://www.travelmath.com/
https://simplemaps.com/data/us-cities
Wikipedia
REFERENCES
Any Questions?
Editor's Notes
Initially, we had 4 trailers and we were supposed to transport 5 items, as shown above.
The cost of transport had several dependencies as shown above.
We assigned weights to every node(Major City) and applied Dijkstra’s algorithm to calculate the shortest distance. This implementation does NOT use a heap, which would be the optimal data structurefor storing unvisited nodes in. So in-place of a heap, it uses a sorted list of this structure:unvisited = [ [distance_to_a, a], [distance_to_b, b] ]It also uses a city_node_lookup dictionary in order to quickly access each of the [distance_to_a, a]lists in O(1) time. It can use this to change the distance to a given node in the unvisitedlist quickly. The unvisited list is re-sorted after each node is visited.
S = Start
N = Node
T = End
Explanation of our computation
