Freight and Fuel Transportation Optimization Tool - Supply Chain Resilience
FTOT is a flexible scenario-testing tool that optimizes the transportation of materials for future energy and freight scenarios. FTOT models and tracks commodity-specific information and can take into account conversion of raw materials to products (e.g., crude oil to jet fuel and diesel) and the fulfillment of downstream demand. FTOT was developed at the US Dept. of Transportation's Volpe National Transportation Systems Center.
FTOT-SCR is a modification of the base FTOT program to support analysis of supply chain resilience. The supply chain resilience assessment includes two parts: integrated risk assessment to capture the combined effects of multiple risk factors on supply chain performance, and resilience assessment to calculate the long-term supply chain resilience in a planning horizon. The supply chain methodology and modifications to the FTOT code were developed at Washington State University (WSU) and utilize the 2022.2 version of FTOT.
Additional documentation developed by the WSU team explains the methodology of the risk assessment and resilience assessment. These files are available in the docs directory.
FTOT-SCR code uses the Python environment created by the main FTOT-Public repository. If you haven't already installed FTOT, follow instructions from the main FTOT landing page to install FTOT, install supporting Python packages, and set up the Python environment.
To install the FTOT-SCR code, clone this repository or download and unzip the code to a directory called C:\FTOT-SCR
. This is the same process as used to download the FTOT code but with a different target directory.
After downloading the FTOT-SCR code, navigate to the \scenarios\ForestResiduals_SCR\input_GISdata
directory and un-zip the facilities.gdb.zip
ZIP File there to the same directory (using the "Extract Here" option), so that the directory contains a folder called facilities.gdb
.
If you encounter an issue extracting the facilities ZIP file, try downloading the file again directly from GitHub here and extracting to the same input_GISdata
folder.
The scenarios\ForestResiduals_SCR
directory contains two batch files: setup_v5_1.bat and run_v5_1.bat. To get started, first run the setup_v5_1.bat
file. This will initiate several Python scripts that will take the inputs described below to create several scenarios. Note that the setup script will take several hours or days to run.
After finishing the set up scripts, run the batch file called run_v5_1.bat
in the scenarios\ForestResiduals-SCR
directory. This will begin a lengthy FTOT run consisting of a single run through FTOT's S, C, F, and G steps, followed by the OSCR step, which executes many runs of the O1 and O2 steps as determined by the number of scenarios, years, and earthquake events in the input files. These runs may take many days, or even weeks, depending on the scale of the analysis.
- If desired, a user can reduce the number of scenarios and years in each scenario by modifying the
N
andplan_horizon
variables in theftot_scr.py
file in the/program
folder. The default value is 30 scenarios, each 20 years long.
FTOT-SCR’s setup_v5_1.bat
file runs a sequence of six set up scripts. The inputs and outputs for each script are included in the table below. The output files of each script either serve as an input for a later script or are inputs necessary to run an FTOT-SCR scenario.
File | Inputs | Outputs |
---|---|---|
1_SeismicEvents.py |
faultdata.xlsx point.txt |
seismic_catalog.npy |
2_Scenario_Generation.py |
FaultData.xlsx point.txt seismic_catalog.npy |
earthquake_events.npy scenario_GFT.npy scenario_forest.npy scenario_earthquake.npy |
3_FacilityCapacity.py |
rmp.csv proc.csv dest.csv rmp_Xycoordinate.txt proc_Xycoordinate.txt dstXYcoordinate.txt Earthquake files |
facility_cap.npy facility_cap_noEarthquake.npy facility_DS.npy CatalystReplace_cost.npy |
4_BridgeDamage.py |
seismic_catalog.npy earthquake_events.npy HighwayBridge_3state.txt MiddlePoint_Road.txt bridge_location.npy Earthquake files |
BDI.npy bridge_DS.npy |
5_EdgeCapacity.py |
HighwayBridge_3state.txt Relationship_BridgeRoad_3_state.txt MiddlePoint_Road.txt earthquake_events.npy BDI.npy bridge_ds.npy |
edge_cap.npy |
6_RepairTimeCost.py |
Relationship_BridgeRoad_3state.txt seismic_catalog.npy earthquake_events.npy BDI.npy bridge_DS.npy edge_cap.npy facility_cap.npy facility_DS.npy |
repair_costs.npy repair_time_edge.npy repair_time_facility.npy total_repair_time.npy |
As each scenario finishes, several summary statistics will be printed in the command line and logged. After a full run of the FTOT-SCR tool, the resilience results from the full suite of scenarios can be viewed through the Numpy files:
Resilience.npy
for the overall resilience metric.R1.npy
andweight1.npy
for the value and weight of hazard-induced losses,R2.npy
andweight2.npy
for the value and weight of non-hazard-induced losses,R3.npy
andweight3.npy
for the value and weight of opportunity-induced gains.
- Add bugs and feature requests to the Issues tab for the Volpe Development Team to triage.
Supply Chain Resilience Scenario and FTOT Modifications
- Dr. Ji Yun Lee (WSU)
- Jie Zhao (WSU)
FTOT
- Dr. Kristin Lewis (Volpe) Kristin.Lewis@dot.gov
- Sean Chew (Volpe)
- Olivia Gillham (Volpe)
- Kirby Ledvina (Volpe)
- Mark Mockett (Volpe)
- Alexander Oberg (Volpe)
- Matthew Pearlson (Volpe)
- Samuel Rosofsky (Volpe)
- Kevin Zhang (Volpe)
The development of FTOT that contributed to this public version was funded by the U.S. Federal Aviation Administration (FAA) Office of Environment and Energy and the Department of Defense (DOD) Office of Naval Research through Interagency Agreements (IAA) FA4SCJ and FB48CS-FB48CY under the supervision of FAA’s Nathan Brown and by the U.S. Department of Energy (DOE) Office of Policy under IAA VXS3A2 under the supervision of Zachary Clement. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the FAA nor of DOE.
The FTOT team thanks our beta testers and collaborators for valuable input during the FTOT Public Release beta testing, including Dane Camenzind, Kristin Brandt, and Mike Wolcott (Washington State University), Mik Dale (Clemson University), Emily Newes and Ling Tao (National Renewable Energy Laboratory), Seckin Ozkul, Robert Hooker, and George Philippides (Univ. of South Florida), and Chris Ringo (Oregon State University).
This project is licensed under the terms of the FTOT End User License Agreement. Please read it carefully.