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‎README.md

+43-9
Original file line numberDiff line numberDiff line change
@@ -1,16 +1,29 @@
11
# DynamicPlacementGenerator
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## Installations
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The DynamicPlacementGenerator is a Python program used to generate the best spare engine placement for a specific aircraft fleet.
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Install `python3`. Check the version and you should see the same as the output below or a more recent version.
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## Background
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Delta Air Lines is an industry-leading, globally operating United States airline servicing over 300 destinations with a fleet of approximately 900 aircraft. Delta’s Engine Demand Planning team (EDP), which falls under Delta TechOps, is responsible for planning engine removals, assigning spare engines to seven designated hubs, and setting up the logistics of the removals and repairs of these engines.
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The objective of this project is to assist Delta’s EDP team with improving the allocation of spare engines across the contiguous United States. To assist Delta in decreasing both transportation and AOS costs incurred throughout the year, the solution determines the optimal configuration of all spare engines on a monthly basis through a Markov Decision Process. The solution outputs a configuration recommendation for the upcoming month associated with the minimal cost of all possible options. Delta’s EDP team can use the model to make data-informed, cost-driven decisions with the added benefit of reducing required labor hours.
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## Installations and Setup
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Instructions to install the required installations are outlined below with provided terminal commands.
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### Before Cloning this Repository
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Install `python3`. Check that your version matches the one below or is more recent.
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```
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python3 --version
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Python 3.7.6
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```
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Install `pip3`. Check that you have it by running the command below to check the version.
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Install `pip3`. Check that you have it by running the command below to check the version. You should see a response similar to the one below.
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```
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pip3 -V
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pip 19.3.1 from /usr/local/lib/python3.7/site-packages/pip (python 3.7)
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```
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Install `numpy` using `pip3`.
@@ -28,27 +41,35 @@ Install `scipy` using `pip3`.
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pip3 install scipy
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```
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Clone this repository.
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### After Cloning this Repository
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After doing that, navigate to the `DynamicPlacementGenerator` directory (wherever you cloned it on your machine) and clone the Git repository for `pymdptoolbox` with the following terminal command:
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Navigate to the `DynamicPlacementGenerator` directory (wherever you cloned it on your machine).
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This application uses the [`pymdptoolbox` module](https://github.com/sawcordwell/pymdptoolbox "Markov Decision Process (MDP) Toolbox for Python"). Clone the repository for it with the following command. **Make sure you are cloning the repository while in the `DynamicPlacementGenerator` directory.**
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```
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git clone https://github.com/sawcordwell/pymdptoolbox.git
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```
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Navigate to the `pymdptoolbox`.
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Navigate to the `pymdptoolbox` folder, which now resides in the `DynamicPlacementGenerator` directory.
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```
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cd pymdptoolbox
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```
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Install `pymdptoolbox` using the following terminal command (while in the `pymdptoolbox` directory):
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Setup and install `pymdptoolbox` using the following terminal command (while in the `pymdptoolbox` directory):
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```
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python3 setup.py install
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```
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## To run locally
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## Usage
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### First Run
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Some files will need to be created to use for all subsequent runs. Most of these tasks will only need to be completed once.
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### Subsequent Runs
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Clone this repository onto your local machine.
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Navigate to the `DynamicPlacementGenerator` directory.
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In your terminal, run the following command:
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```
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python3 app.py
@@ -65,3 +86,16 @@ max removals total that can occur = 10
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max total working engines = 5
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changing all inputs and re-running all possible removal situations adds time to the run time. It took me about 1 hour and 30 minutes to generate all possible removal situations for all fleets.# DynamicPlacementGenerator
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## Authors
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**Industrial and Systems Engineering, Georgia Institute of Technology**, Spring 2020
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**Team 10**
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Samantha Davanzo
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Brian Davis
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Mary Elizabeth Davis
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Bella Jackson
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Meredith Thacker
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Miles Trumbauer
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‎__init__.py

Whitespace-only changes.

‎app.py

+34-37
Original file line numberDiff line numberDiff line change
@@ -1,61 +1,58 @@
1-
from util import reader_util, writer_util, data_util
2-
import data, solve, generate_removal_situations
1+
from util import reader_util, writer_util, data_util, config
2+
from services import data_generator, solve
3+
import data
34
import pprint, logging
4-
from solve import FiniteHorizonMDPSolver
55

66
if __name__ == '__main__':
77
data.init()
8-
logging.basicConfig(level=logging.INFO)
9-
new_removal_data = False
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if config.first_run:
10+
logging.info("FIRST_RUN is set to TRUE. All possible states and actions are going to be generated. This may take awhile.")
11+
data_generator.generate_all_possible_states()
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data_generator.generate_all_possible_actions()
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# Import removal information
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data.removals_info, data.aos_cost = reader_util.import_removal_info(
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filepath='data_to_read/removal_info.csv',
17+
removals_data_storage=data.removals_info,
18+
aos_cost_data_storage=data.aos_cost)
19+
20+
# Import engine information
21+
data.engines_info = reader_util.import_engine_info(
22+
filepath='data_to_read/engine_info.csv',
23+
data_storage=data.engines_info)
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25+
# Import engine subtype data
26+
reader_util.import_engine_subtype_data()
27+
28+
# Generate all possible removal situations if removal info has been updated
29+
for engine_subtype in data.engine_subtypes:
30+
if data.need_to_update_removal_info[engine_subtype]:
31+
data_generator.generate_all_possible_removal_situations(
32+
engine_subtype=engine_subtype)
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1134
# Import all possible states
1235
data.all_possible_states = reader_util.import_all_possible_states(
13-
filepath='data_to_read/general/all_possible_states.csv',
36+
filepath='data_to_read/all_possible_states.csv',
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data_storage=data.all_possible_states)
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# Import all possible actions
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data.all_possible_actions = reader_util.import_all_possible_actions(
1841
data_storage=data.all_possible_actions)
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20-
# Import engine removal information
21-
data.num_engines_info, data.num_removals_info, data.aos_cost = reader_util.import_engine_removal_info(
22-
filepath='data_to_read/general/engine_removal_info.csv',
23-
engines_data_storage=data.num_engines_info,
24-
removals_data_storage=data.num_removals_info,
25-
aos_cost_data_storage=data.aos_cost)
26-
27-
# Import engine subtype data
28-
reader_util.import_engine_subtype_data()
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30-
# Generate all possible removal situations
31-
if new_removal_data:
32-
for engine_subtype in data.engine_subtypes:
33-
generate_removal_situations.find_all_removal_situations(
34-
engine_subtype=engine_subtype,
35-
removals_info=data.num_removals_info[engine_subtype])
43+
data_util.minimize_states_and_actions_to_iterate()
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3745
# Import all possible removal situations
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data.all_possible_removal_situations = reader_util.import_all_possible_removal_situations(
3947
data_storage=data.all_possible_removal_situations)
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# Import future data for regression
4250
reader_util.import_future_data()
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44-
havent_done = ['CFM56-5A']
45-
for month_to_run in range(1, 11):
46-
for engine_subtype in data.engine_subtypes:
47-
if engine_subtype in ['PW2000-2037', 'V2500-D5']:
48-
num_engines = data.num_engines_info[engine_subtype]['NUM_WORKING_ENGINES']
49-
if num_engines >= 5:
50-
all_possible_actions_for_subtype = data_util.find_all_possible_actions_for_subtype(
51-
num_engines=num_engines,
52-
num_removals_info=data.num_removals_info[engine_subtype])
53-
solver = FiniteHorizonMDPSolver(engine_subtype, all_possible_actions_for_subtype, month_to_run)
54-
solver.solve_MDP()
55-
else:
56-
solver = FiniteHorizonMDPSolver(engine_subtype, data.all_possible_actions[num_engines][:], month_to_run)
57-
solver.solve_MDP()
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# Solve Finite Horizon MDP
53+
for engine_subtype in data.engine_subtypes:
54+
solver = solve.FiniteHorizonMDPSolver(engine_subtype)
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solver.solve_MDP()
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‎data.py

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Original file line numberDiff line numberDiff line change
@@ -41,6 +41,9 @@ def init():
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global all_possible_states
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all_possible_states = {}
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global states_by_subtype
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states_by_subtype = {}
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4447
'''
4548
A dictionary that holds all possible actions in the MDP as a list of lists for each engine subtype.
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global all_possible_actions
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all_possible_actions = {}
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57+
global actions_by_subtype
58+
actions_by_subtype = {}
59+
5460
'''
5561
A dictionary that holds all possible removal situations as a list of lists for each engine subtype.
5662
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7884
'NUM_WORKING_ENGINES': 4,
7985
'TOTAL_NUM_ENGINES': 4}, ...}
8086
'''
81-
global num_engines_info
82-
num_engines_info = {}
87+
global engines_info
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engines_info = {}
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8490
'''
8591
A dictionary that holds information for the number of removals for each engine subtype.
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108114
'MAX_NUM_REMOVALS_MONTHLY_SLC': 1,
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'MAX_NUM_REMOVALS_MONTHLY_TOTAL': 2}, ...}
110116
'''
111-
global num_removals_info
112-
num_removals_info = {}
117+
global removals_info
118+
removals_info = {}
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114120
'''
115121
A dictionary that holds the default expected AOS cost for each engine subtype.
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224230
global total_RONSRADS_ground_time_by_hub_monthly
225231
total_RONSRADS_ground_time_by_hub_monthly = {}
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233+
global need_to_update_removal_info
234+
need_to_update_removal_info = {}
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‎data_to_read/BR700-715C1-30/BR700-715C1-30_num_departures_by_hub_monthly.csv

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YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
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2019-01,2158,10,1006,561,927,421,599,6459
3+
2019-02,1819,1,946,497,903,361,569,5728
4+
2019-03,2636,0,1092,458,1098,334,484,6966

‎data_to_read/BR700-715C1-30/BR700-715C1-30_total_RONSRADS_ground_time_by_hub_monthly.csv

+4
Original file line numberDiff line numberDiff line change
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YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,26159,2606,42975,11590,28155,38375,34586,975834
3+
2019-02,26186,0,38942,13302,23726,41318,24810,864140
4+
2019-03,19740,0,41651,11578,32192,22765,21517,921071

‎data_to_read/BR700-715C1-30/BR700-715C1-30_total_departures_ground_time_by_state_region_monthly.csv

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Original file line numberDiff line numberDiff line change
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YEAR-MONTH,ATL,DTW,SEA,MSP,SLC,CVG,LAX,WA,OR,ID-MT,NCA,SCA,NV-AZ-TX,NM-CO,WY,MT,ID,NV-UT,ND,MN,SD-NE,KS-MO,IA-IL,AR-OK,WI-MI,WI,TX,AR-LA,LA,MS,AL,GA,SC,TN,NC,VA,NFL,SFL,IL,IN,MO-AR,KY-OH,WV-VA,IL-IN-MI,MI,OH,MD-VA-PA,DE-NJ-PA,PA,SNY,NNY,CT-RI-MA,NH-VT-ME
2+
2019-01,157097,115222,70440,104894,74945,3661,45939,12329,21345,0,97561,37653,60299,49201,0,12931,0,0,15084,0,44,37808,2145,6993,1499,7212,104258,0,32057,3194,5586,42597,66194,50401,155196,587,17104,11180,0,16022,12778,22248,28929,67347,0,4694,9424,66253,15631,148156,20819,85768,633
3+
2019-02,133533,102218,62830,91832,64801,454,40464,10008,17812,0,89436,34502,58938,44570,0,13414,0,0,16394,0,39,36400,0,14637,0,4300,91256,0,31089,1045,3341,48170,61552,49821,152226,0,10594,1559,0,12146,12536,16087,32948,48699,0,0,7233,61377,13128,109544,15032,85838,0
4+
2019-03,183058,114291,45626,108003,50719,0,34862,9652,8162,0,70190,23735,42546,37389,0,30505,0,0,28530,0,13695,40698,0,31573,29501,4160,142667,0,35787,1877,24593,130,53058,30514,150990,0,42905,15709,0,15847,5061,0,20040,88830,0,0,17227,99306,14396,120820,39984,19442,446

‎data_to_read/CF6-80C2B8F/CF6-80C2B8F_num_departures_by_hub_monthly.csv

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YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,210,0,0,87,0,0,3,257
3+
2019-02,177,0,0,77,2,0,1,247
4+
2019-03,230,0,0,73,10,0,0,269

‎data_to_read/CF6-80C2B8F/CF6-80C2B8F_total_RONSRADS_ground_time_by_hub_monthly.csv

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YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,95821,0,0,25505,0,0,0,80561
3+
2019-02,65275,0,0,20298,0,0,0,105855
4+
2019-03,70246,0,0,24571,8932,0,0,57819

‎data_to_read/CF6-80C2B8F/CF6-80C2B8F_total_departures_ground_time_by_state_region_monthly.csv

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1+
YEAR-MONTH,ATL,DTW,SEA,MSP,SLC,CVG,LAX,WA,OR,ID-MT,NCA,SCA,NV-AZ-TX,NM-CO,WY,MT,ID,NV-UT,ND,MN,SD-NE,KS-MO,IA-IL,AR-OK,WI-MI,WI,TX,AR-LA,LA,MS,AL,GA,SC,TN,NC,VA,NFL,SFL,IL,IN,MO-AR,KY-OH,WV-VA,IL-IN-MI,MI,OH,MD-VA-PA,DE-NJ-PA,PA,SNY,NNY,CT-RI-MA,NH-VT-ME
2+
2019-01,129740,0,0,0,231,0,43036,0,0,0,3618,60,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,109820,0,0,0
3+
2019-02,87964,0,0,180,64,0,30825,0,0,0,1526,210,150,900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,180,90,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,131421,0,200,0
4+
2019-03,102458,0,0,9025,0,0,30505,0,122,0,1803,195,1170,0,0,0,0,0,0,0,0,120,0,0,0,0,0,0,120,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,82881,0,0,0

‎data_to_read/CFM56-5A/CFM56-5A_expected_transport_cost.csv

+54
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1+
STATE REGION,ATL,CVG,DTW,LAX,MSP,SEA,SLC
2+
ATL,0,5838.06,6369.27,8939.58,6824.16,9455.82,7920.22
3+
CVG,5978.16,0,5534.79,8920.22,6208.56,8931.26,7546.3
4+
DTW,6487.02,5502.06,0,9068.06,6158.34,8941.22,7564.54
5+
LAX,9403.56,8742.78,9225.9,0,8189.82,6925.98,6131.18
6+
MSP,7219.62,6242.94,6294.24,8464.38,0,7834,6944.38
7+
SEA,10300.5,8972.94,9332.04,7037.02,7765.38,0,6327.26
8+
SLC,8789.76,7805.34,8078.49,6303.1,7070.4,6462.84,0
9+
AL,5482.31,5942.46,6484.04,8666.53,6768.85,9337.96,7794.93
10+
AR-LA,6177.74,6245.63,6769.31,7963.84,6485.9,8817.38,7257.5
11+
AR-OK,6696.9,6418.5,6842.33,7543.02,6260.81,8379.73,6874.84
12+
CT-RI-MA,7218.77,6528.3,6446.91,10344.56,7333.3,10145.19,8665.67
13+
DE-NJ-PA,6678.68,6061.5,6092.21,9880.12,6952.14,9754.95,8308.12
14+
GA,5442.72,6109.47,6635.64,9194.58,7125.66,9764.03,8203.78
15+
IA-IL,6760.26,5924.16,5989.09,8226.78,5468.63,8085.08,6836.84
16+
ID,9118.04,8084.22,8381.9,6555.13,7187.04,6154.74,5431.68
17+
ID-MT,9560.64,8317.18,8596.38,7196.01,7114.14,5787.22,5953.34
18+
IL,6246.78,5623.02,5931.9,8384.01,5870.52,8494.13,7085.74
19+
IL-IN-MI,6511.44,5549.66,5416.45,8781.18,5882.67,8658.74,7316.02
20+
IN,6090.62,5339.1,5668.01,8673.47,6056.6,8741.69,7349.31
21+
KS-MO,6803.82,6187.5,6565.08,7784.67,5882.94,8092.3,6643.72
22+
KY-OH,6003.9,5260.62,5590.74,8888.54,6278.91,9014.02,7563.24
23+
LA,6091.42,6477.47,7066.5,8288.03,6939.5,9237.7,7595.24
24+
MD-VA-PA,6415.34,5955.32,6020.84,9791.07,6889.28,9690.21,8248.84
25+
MI,6760.7,5737.26,5355.06,9150.78,6080.04,8793.66,7634.97
26+
MN,7565.84,6479.1,6551.49,8516.93,5386.97,7746.02,7014.3
27+
MO-AR,6245.46,5830.92,6237.51,8168.26,5994.32,8524.15,7068.26
28+
MS,5747.35,6099.42,6654.23,8438.48,6695.95,9218.91,7638.8
29+
MT,9005.58,7873.38,8111.43,7095.69,6685.92,6185.62,5752.95
30+
NC,5812.43,5947.76,6322.06,9528.65,7055.66,9847.91,8309.19
31+
NCA,9877.18,8998.48,9402.68,5660.7,8264.02,6409.06,6183.77
32+
ND,8039.84,6864.12,6970.88,8105.78,5675.99,7233.5,6655.2
33+
NFL,5733.9,6376.27,6930.25,9200.54,7308.69,9923.49,8328.69
34+
NH-VT-ME,7433.46,6672.6,6495.54,10451.42,7431.66,10245.98,8758.12
35+
NM-CO,7974.99,7258.08,7635.4,6703.28,6797.23,7242.63,5794.31
36+
NNY,6920.64,6022.86,5863.93,9771.05,6805.41,9604.51,8170.8
37+
NV-AZ-TX,8555.38,8098.29,8594.32,5918.76,7645.7,7393.89,6055.18
38+
NV-UT,9139.03,8176.96,8505.25,5984.89,7490.3,6574.72,5470.68
39+
OH,6488.01,5502.9,5380.61,9246.26,6322.37,9109.3,7717.68
40+
OR,10174.77,8981.76,9358.58,6542.9,8001.09,5540.71,6178.3
41+
PA,6566.62,5755.4,5715.59,9538.68,6619.07,9413.32,7995.61
42+
SC,5574.74,5982.12,6425.09,9372.1,7090.65,9832.23,8266.02
43+
SCA,9335.84,8660.63,9184.18,139.66,8153.53,7018.94,6096.52
44+
SD-NE,7379.67,6532.74,6638.89,7780.62,5664.51,7545.44,6424.54
45+
SFL,6214.18,6811.62,7422.8,9760.27,7762.63,10417.29,8801.52
46+
SNY,6859.66,6208,6196.52,10030.43,7044.48,9849.24,8394.76
47+
TN,5556.42,5601.46,6111.55,8735.71,6529.59,9178.32,7667.14
48+
TX,6742.66,6824.97,7426.6,7650.48,6890.58,8707.16,7114.28
49+
VA,6205.46,6035.63,6284.36,9805.5,7121.92,9928.59,8413.61
50+
WA,10090.62,8804.38,9148.43,7088.65,7603.38,5315.12,6245.69
51+
WI,6868.37,5872.33,5890.54,8629.12,5450.4,8203.85,7165.69
52+
WI-MI,7078.64,6061.84,5937.76,8918.11,5556.02,8283.86,7411.63
53+
WV-VA,6072.8,5604.2,5885.05,9386.27,6714.97,9511.93,8018.11
54+
WY,8454.35,7507.64,7730.42,6909.95,6563.99,6688.6,5626.84

‎data_to_read/CFM56-5A/CFM56-5A_num_departures_by_hub_monthly.csv

+4
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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,1513,130,855,374,1152,372,735,6107
3+
2019-02,1470,137,782,342,1108,343,654,5818
4+
2019-03,1725,90,1186,508,1328,383,816,7562

‎data_to_read/CFM56-5A/CFM56-5A_number_of_broken_engines_and_number_repaired.csv

+9
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@@ -0,0 +1,9 @@
1+
,1,2,3,4,5,6,7
2+
0,0.60653066,0.367879441,0.22313016,0.135335283,0.082084999,0.049787068,0.030197383
3+
1,0.39346934,0.367879441,0.33469524,0.270670566,0.205212497,0.149361205,0.105690842
4+
2,,0.264241118,0.25102143,0.270670566,0.256515621,0.224041808,0.184958973
5+
3,,,0.19115317,0.180447044,0.213763017,0.224041808,0.215785469
6+
4,,,,0.142876541,0.133601886,0.168031356,0.188812285
7+
5,,,,,0.10882198,0.100818813,0.1321686
8+
6,,,,,,0.083917942,0.07709835
9+
7,,,,,,,0.065288098

‎data_to_read/CFM56-5A/CFM56-5A_regression.csv

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1+
Hub/Region,RR coeff,D coeff,intercept
2+
ATL,0.000041,-0.001463,-0.933
3+
CVG,0.00008,0.0081,-5.56
4+
DTW,0.00003,-0.00175,-0.51
5+
LAX,,,
6+
MSP,-0.000005,0.001299,-1.86
7+
SEA,,,
8+
SLC,-0.000004,0.001359,-1.37
9+
OTHER,0.000011,0.00062,-21.5

‎data_to_read/CFM56-5A/CFM56-5A_total_RONSRADS_ground_time_by_hub_monthly.csv

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1+
YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,65178,67662,78108,10627,114088,45846,51596,1118704
3+
2019-02,67848,68424,75257,3974,113285,43551,44902,1081240
4+
2019-03,32241,28926,79431,19168,88770,20231,26558,1215234

‎data_to_read/CFM56-5A/CFM56-5A_total_departures_ground_time_by_state_region_monthly.csv

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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,DTW,SEA,MSP,SLC,CVG,LAX,WA,OR,ID-MT,NCA,SCA,NV-AZ-TX,NM-CO,WY,MT,ID,NV-UT,ND,MN,SD-NE,KS-MO,IA-IL,AR-OK,WI-MI,WI,TX,AR-LA,LA,MS,AL,GA,SC,TN,NC,VA,NFL,SFL,IL,IN,MO-AR,KY-OH,WV-VA,IL-IN-MI,MI,OH,MD-VA-PA,DE-NJ-PA,PA,SNY,NNY,CT-RI-MA,NH-VT-ME
2+
2019-01,177923,152216,70208,205060,112142,81676,35493,2317,17334,33335,22578,38272,6021,30442,21295,15858,0,124,0,0,26580,19215,10785,0,0,40,226263,0,34367,0,0,0,0,15389,45626,0,48633,162624,0,21928,1734,24141,20351,37715,0,558,146965,9800,30187,332073,2326,145925,0
3+
2019-02,183060,142653,67983,199343,97002,83835,27493,2284,16016,31414,20816,36520,5448,29551,20914,14901,0,0,0,0,23807,17944,434,0,0,0,218947,0,34891,0,0,0,0,10938,44052,0,35574,170463,0,20634,1825,28425,19332,42289,0,0,152039,9800,28599,316094,0,141381,0
4+
2019-03,161088,171583,44509,192652,82028,38592,49499,20333,24392,23538,34441,37492,25848,18018,25832,18407,0,0,19054,0,25698,18296,13800,0,0,12073,211500,0,44482,0,0,0,12645,39432,71098,0,35065,163976,0,21292,13212,14640,19650,69543,0,24770,111075,447,16566,341387,22380,142864,13515

‎data_to_read/CFM56-5B3-3/CFM56-5B3-3_num_departures_by_hub_monthly.csv

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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,2221,0,590,230,476,1,344,3716
3+
2019-02,2061,0,550,189,427,0,292,3444
4+
2019-03,2135,30,737,272,727,0,374,4705

‎data_to_read/CFM56-5B3-3/CFM56-5B3-3_total_RONSRADS_ground_time_by_hub_monthly.csv

+4
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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,134902,0,66137,27900,65575,0,36456,611406
3+
2019-02,129284,0,62172,26555,48930,0,39243,571919
4+
2019-03,91396,431,32773,21107,60068,0,40568,664282

‎data_to_read/CFM56-5B3-3/CFM56-5B3-3_total_departures_ground_time_by_state_region_monthly.csv

+4
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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,DTW,SEA,MSP,SLC,CVG,LAX,WA,OR,ID-MT,NCA,SCA,NV-AZ-TX,NM-CO,WY,MT,ID,NV-UT,ND,MN,SD-NE,KS-MO,IA-IL,AR-OK,WI-MI,WI,TX,AR-LA,LA,MS,AL,GA,SC,TN,NC,VA,NFL,SFL,IL,IN,MO-AR,KY-OH,WV-VA,IL-IN-MI,MI,OH,MD-VA-PA,DE-NJ-PA,PA,SNY,NNY,CT-RI-MA,NH-VT-ME
2+
2019-01,296967,117668,75,105997,69660,0,51574,0,0,0,0,47062,140419,0,0,12604,0,0,0,0,0,0,0,0,0,1218,64391,0,0,0,0,0,0,0,4301,0,47303,243236,0,0,0,0,0,0,0,0,40113,0,0,208063,0,86580,0
3+
2019-02,282130,106349,0,86604,66348,0,45686,0,0,0,0,40112,124806,0,0,11388,0,0,0,0,0,0,0,0,0,1276,67148,0,0,0,0,0,0,0,0,0,44300,228143,0,0,0,0,0,0,0,0,36705,0,0,198544,0,90023,0
4+
2019-03,245478,89102,0,110454,69233,2385,38947,0,0,0,0,91350,164983,0,0,12640,0,0,0,0,0,540,0,0,0,20007,74522,0,0,0,0,0,0,2052,27513,0,77956,170183,0,12625,0,0,0,0,0,0,42015,0,0,199984,0,99529,0

‎data_to_read/CFM56-7B26/CFM56-7B26_num_departures_by_hub_monthly.csv

+4
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@@ -0,0 +1,4 @@
1+
YEAR-MONTH,ATL,CVG,DTW,LAX,MSP,SEA,SLC,OTHER
2+
2019-01,1131,240,216,810,364,698,1015,2883
3+
2019-02,1013,217,198,764,371,637,912,2542
4+
2019-03,1525,407,174,681,593,783,945,3422

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