Abstract
This model is part of an LDRD effort to investigate the connection of food and agriculture supply chain and the critical infrastructure. The model was built for a small number of farmers, shippers, processing companies and retailers as proof of concept to illustrate supply chain impacts. In this model, the emphasis is on understanding the climate change impacts on the food supply chain. The model uses agent-based modeling method in combination with machine learning. It also connects logistic simulation with economic principles such as price change caused by supply and demand, and consumer substitution effect based on price comparisons of two substitutable commodities.
- Developers:
- Release Date:
- 2022-12-29
- Project Type:
- Closed Source
- Software Type:
- Scientific
- Sponsoring Org.:
-
USDOE Office of Nuclear Energy (NE)Primary Award/Contract Number:AC07-05ID14517
- Code ID:
- 99653
- Research Org.:
- Idaho National Laboratory (INL), Idaho Falls, ID (United States)
- Country of Origin:
- United States
- Keywords:
- agriculture logistics; supply chain; disruptions; market dynamics, climate change
Citation Formats
Nguyen, Thuy, Lee, Yuan-Yuan, and Rahman, Mamunur M.
Food And Agriculture Supply Chain Model.
Computer Software.
USDOE Office of Nuclear Energy (NE).
29 Dec. 2022.
Web.
doi:10.11578/dc.20230314.11.
Nguyen, Thuy, Lee, Yuan-Yuan, & Rahman, Mamunur M.
(2022, December 29).
Food And Agriculture Supply Chain Model.
[Computer software].
https://doi.org/10.11578/dc.20230314.11.
Nguyen, Thuy, Lee, Yuan-Yuan, and Rahman, Mamunur M.
"Food And Agriculture Supply Chain Model." Computer software.
December 29, 2022.
https://doi.org/10.11578/dc.20230314.11.
@misc{
doecode_99653,
title = {Food And Agriculture Supply Chain Model},
author = {Nguyen, Thuy and Lee, Yuan-Yuan and Rahman, Mamunur M.},
abstractNote = {This model is part of an LDRD effort to investigate the connection of food and agriculture supply chain and the critical infrastructure. The model was built for a small number of farmers, shippers, processing companies and retailers as proof of concept to illustrate supply chain impacts. In this model, the emphasis is on understanding the climate change impacts on the food supply chain. The model uses agent-based modeling method in combination with machine learning. It also connects logistic simulation with economic principles such as price change caused by supply and demand, and consumer substitution effect based on price comparisons of two substitutable commodities.},
doi = {10.11578/dc.20230314.11},
url = {https://doi.org/10.11578/dc.20230314.11},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20230314.11}},
year = {2022},
month = {dec}
}