EAGER: SSDIM: Generating Synthetic Data on Interdependent Food, Energy, and Transportation Networks via Stochastic, Bi-level Optimization

点击翻译按钮获取中文摘要

This EArly-concept Grant for Exploratory Research (EAGER) project will generate data at the interdependencies of the energy, food, and transportation infrastructures, providing essential information for contributing to improved approaches to addressing design and operational issues for interdependent critical infrastructures (ICIs). The project introduces a new mathematical framework and applies it to data generation, allowing explicit representation of infrastructure interdependencies. It allows integration of current data generation techniques into a unified representation of societal, mechanistic, and physical aspects of ICIs. All data generated from this research will be made freely available through online repositories. Along with academic publications and presentations, the project will create communication materials such as digital maps for dissemination to practitioners, particularly within rural communities. The findings and outcomes from this research may serve to raise public awareness about infrastructure threats and resilience. This project will also develop a food/energy module for elementary schoolchildren, as well as support for graduate student researchers.This project will develop a new mathematical framework (Stochastic Bilevel Optimization) to generate synthetic data on ICIs. The project will also provide uncertainty measures associated with these data, allowing a measure of quality as well as quantifying relationships with input information. This method will generate data for interdependent agriculture, food, energy, and transportation ICIs, allowing for integration of existing data generation techniques. The mathematical structure of the stochastic bilevel optimization problem allows for representation of, and integration across, the physical, mechanistic, and community functions of ICIs. The aim is to generate data to optimize strategies for disaster preparedness, resilience, and response. This research will contribute to the emerging area of food system resilience and will enable future efforts to model potential threats to food systems such as energy supply disruptions and fuel price spikes.