Optimal Sequencing of Projects with Uncertain Regulatory Costs; Societal Impacts of Going to Mars

Author:
Woods, Christopher, School of Engineering and Applied Science, University of Virginia
Advisors:
Krzysztofowicz, Roman, EN-SIE, University of Virginia
JACQUES, RICHARD, EN-Engineering and Society, University of Virginia
Abstract:

The technical portion of my project produced a decision system that integrates judgmental forecasting and statistical cost analysis to quantify the uncertainty within a stochastic optimization model to support compliance planning. The model fully quantifies the uncertainty about future project costs, changes in compliance metrics, and the costs of mitigation strategies to minimize the expected cost of achieving a compliance target.
The judgmental forecasting procedure features expert/user assessment of three quantiles for each uncertain input variable. These assessments are used to estimate parametric distributions, enabling complete quantification of uncertainty. Where available, historical data supplements the expert's judgment, our paper used statistical analysis of carbon offset futures to provide credible intervals to guide quantile assessment for the cost of carbon emission mitigation instruments. Our project is covered by a non-disclosure agreement, but the methodology developed can be applied to many use cases.
In my STS research, I developed an argument for more careful consideration of the effects of a reinvigoration of space travel technological development under the STS theories of latent and manifest functions and dysfunctions and sociotechnical imaginaries. I broke down the history of space travel and how space travel interacted with foreign relations. I then discussed the current state of space travel to ponder what a hypothetical mission would do to the rest of our society. This journey would influence our society—not only technologically, but across social, political, economic, and cultural domains. I argue that this process would have far-reaching consequences, greater than many people currently anticipate.

Degree:
BS (Bachelor of Science)
Keywords:
stochastic optimization, bayesian, judgmental forecasting, Mars, space travel
Notes:

School of Engineering and Applied Science

Bachelor of Science in Systems Engineering

Technical Advisor: Roman Krzysztofowicz

STS Advisor: Richard Jacques

Technical Team Members: Malek Thabet, Mitch Mitchell

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2025/05/06