Quantum Annealing Applied to an Industrial Problem
June 3 (Thursday), 2021
11:30 am to 12:30 pm (EDT)
Virtual via Zoom
Abstract: After introducing the industrial problems at GE Research we will focus on asset sustainment. Superior supply chain capabilities can be a critical lever for a business to have over its competitors. Ideally these operations are planned to maximize an objective function, but as these are NP-hard problems, closed form solutions quickly scale in complexity beyond the ability of classical methods to provide a timely and optimal answer. To overcome this obstacle, we took advantage of Adiabatic Quantum Computing and Quantum Annealing and formulated the problem in the Quadratic Unconstrained Binary Optimization framework. In this talk we will describe how we formulate a resource allocation problem for asset sustainment as a QUBO, allowing us to globally reduce resource contention and depending on the needs show a choice of different cost function that can lead to different optimality. We will discuss limitations of the approach that will be overcome with changes to graph-embedding strategies and future machine topology as well as analysis on how pausing techniques effects optimality of the optimization problem under investigation.
Annarita Giani is a Senior Complex System Scientist at GE Research. She leads the quantum application group at GE focused on quantum computing algorithm development for industrial applications. She works directly with GE businesses to investigate quantum acceleration of real-world problem. She organized the first workshop on “quantum computing opportunity for renewable energy” during the IEEE Quantum Week 2020. Annarita is interested in critical infrastructure protection, energy systems, supply chain, modeling and simulation for situational awareness, machine learning and optimization for large dynamic, complex problems. Annarita has presented at international conferences and published over 50 articles in international conferences and journals. Before joining GE, Dr. Giani spent four years at Los Alamos National Laboratory working on cybersecurity of the energy grid. She started this research during her postdoc at UC Berkeley. She holds a Ph.D. in Computer Engineering from Thayer School of Engineering at Dartmouth College and a Master’s in Mathematics from the University of Pisa, Italy.
Aussie Schnore is a Senior Principal Engineer and Edge Architect with the GE Research. Aussie has 30+ years’ experience in a wide range of technical domains, including semiconductors, power electronics, embedded systems software development, and advanced computing. He led a ten-year joint GE/Lockheed Martin Shared Vision Project in the advanced computing concepts, formed the global office of Intellectual Protection across GE Research, and is founder/chief architect of GE’s Edge effort. In 2017 Aussie and a team from GE deployed Dispatch Optimizer, the first Industrial Edge App, which anticipated to bring in > $150M in value for GE and its customers by leveraging digital twins in the combined cycle power plant cyber-physical system to optimize the use of turbine life and fuel usage to increase power generation revenue. Currently he is working in the areas of Quantum Computing, and leads an effort in Scene Intelligence within GE Research. Aussie has been on several external boards, advisory councils and has 18 patents in various fields. He holds a B.S. degree in Electrical Engineering from Union College.