Quantum Enhanced Optimization for Industrial-Scale Problems

ORAL

Abstract

Many of the most challenging optimization problems faced by industry today are combinatorial in nature. Quantum computing and related approaches offer new heuristics for tackling these problems that might provide advantages over traditional optimization methods. Establishing such advantages requires benchmarking on specific problem instances. In this work, we consider the production plant optimization problem under realistic conditions. We characterize the problem and carry out a benchmark of multiple classical and quantum-inspired optimizers, including techniques based on generative modeling for quantum enhanced optimization. By comparing classical optimizers, quantum-enhanced optimizers, and mixed optimizers that combine the two, we gain insights into which aspects of the problems influence the performance of the optimizers. In addition, we perform a scaling analysis of the optimization methods and estimate thresholds for advantage.

*This work is funded by the MIT Center for Quantum Engineering

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Presenters

  • William P Banner

    • Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science
    • Massachusetts Institute of Technology MI

Authors

  • William P Banner

    • Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science
    • Massachusetts Institute of Technology MI

  • Tim Menke

    • Harvard University, Massachusetts Institute of Technology Research Laboratory of Electronics
    • Harvard University

  • Shima B Hadiashar

    • Zapata Computing Inc

  • Grzegorz Mazur

    • Zapata Computing Inc, Jagiellonian University Department of Computational Methods in Chemistry

  • Marcin Ziolkowski

    • BMW Group Information Technology Research Center

  • Ken Kennedy

    • BMW Group Information Technology Research Center

  • Jeffrey A Grover

    • Massachusetts Institute of Technology MI
    • Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science
    • Massachusetts Institute of Technology MIT
    • Northrop Grumman - Mission Systems
    • Massachusetts Institute of Technology

  • Jhonathan Romero

    • Zapata Computing Inc

  • William D Oliver

    • Massachusetts Institute of Technology MIT
    • Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Research Laboratory of Electronics
    • MIT Lincoln Laboratory and Department of Electrical Engineering & Computer Science and Department of Physics, Massachusetts Institute of Technology