Chad Uhles
PhD Candidate
UT Knoxville
Friday, November 17, 2023
Tickle 500 1:50-2:40pm
Title: Optimizing the Selection of Resolutions to Part Obsolescence over a Time Horizon
Abstract: Diminishing manufacturing sources and material shortages (DMSMS) is a significant issue in many industries such as aerospace, defense, and nuclear power. Problems caused by DMSMS can arise when crucial systems are extended well beyond their initially anticipated lifetimes and parts become obsolete. To combat this issue, it is important to develop a plan to buy, replace, and refresh parts over time to sustain the system. Indeed, a well-crafted sustainment plan can yield significant cost savings. In this work, we develop a mixed-integer programming model for selecting resolutions of DMSMS issues over time. Possible resolutions include, but are not limited to, part substitutions, lifetime buys, or a full refresh of the current part or system design. We demonstrate our model on a hypothetical system that is subject to obsolescence.
Samuel Affar O.
PhD Candidate
UT Knoxville
Title: Power Grid Resilience Optimization Using Decision-Dependent Uncertainty
Abstract: Extreme weather events can cause unplanned disruptions in power distribution systems, highlighting the need for resilience-oriented action. This ongoing study proposes a two-stage stochastic mixed-integer program with decision-based uncertainty to determine how to optimally protect power distribution systems against such disruptions. In the first stage, a set of lines are hardened. A random set of destroyed lines is then realized. The probability for each element is dependent on the hardening decisions made in the first stage, i.e., decision-dependent uncertainty. In the second stage, network reconfiguration and DERs (Distributed Energy Resources) utilization decisions are made. The model seeks to minimize the expected cost of load shedding. To find a computationally fast way to solve the model, the study explores a decision-independent reformulation.