Quantum Computing in Operations Research

Emily L. Tucker, Mohammadhossein Mohammadisiahroudi

Quantum computing is rapidly emerging as a new computing paradigm with the potential to improve decision-making, optimization, and simulation across industries. For industrial engineering (IE) and operations research (OR), this shift introduces both unprecedented opportunities and substantial challenges. The learning curve is high, and to help researchers navigate the emerging field of quantum operations research, we provide a road map of the current field of quantum operations research. We introduce the foundational principles of quantum computing, outline the current hardware and software landscape, and survey major algorithmic advances relevant to IE/OR, including quantum approaches to linear algebra, optimization, machine learning, and stochastic simulation. We then highlight applied research directions, including the importance of problem domains for driving long-term value of quantum computers and how existing classical OR models can be reformulated for quantum hardware. Recognizing the steep learning curve, we propose pathways for IE/OR researchers to develop technical fluency and engage in this interdisciplinary domain. By bridging theory with application, and emphasizing the interplay between hardware and research development, we argue that industrial engineers are uniquely positioned to shape the trajectory of quantum computing for practical problem-solving. Ultimately, we aim to lower the barrier to entry into quantum computing, motivate new collaborations, and chart future directions where quantum technologies may deliver tangible impact for industry and academia.

Florian Klug

Vladimir I. Hahanov, Svetlana V. Chumachenko, Ivan Hahanov +3 more

Asadullah Khalid, Shahid Tufail, Arif I. Sarwat

Quantum Computing technology is currently prevailing as a promising candidate for expanding the research horizons in the areas of power engineering and transportation. An across-the-board view of this technology identifies that the intersecting research of interest which covers both areas is the identification of innovative energy storage technologies. Quantum Computers (QC) provide the capability to develop an innovative energy storage system, but its operating principles encompass the domains of Quantum Physics (QP) and Quantum Mechanics (QM) and thus limit the understanding of its underlying functionality. The applicable storage system under research using QC, termed Quantum Battery (QB) is considered to be a theoretical construct, which means that it is not directly observable. This paper attempts to piece together the QM and its applications in a QC, directed towards the identification of an innovative QB, by providing a review of the existing researches. Also, the explanations of various postulates and their corresponding formulations leading to the QM framework behind a QB is presented. This is followed by a review of the underlying operation of a QC and its application in performing battery research. A summary of the existing QB researches is also presented which are categorized into particle- and chemistry-driven (quantum) battery researches.

Li Huang

Ojas Parekh

This article highlights synergies between quantum information science (QIS) and operations research for QIS-curious operations researchers (and vice versa), and the author challenges the community to discover more. History: This “Challenge” paper was invited by the Editor in Chief and based on the topics raised by the author at his plenary address at the 2022 INFORMS Computing Society Conference in Tampa, Florida. Funding: This material is based on work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Accelerated Research in Quantum Computing, Fundamental Algorithmic Research for Quantum Computing. This article has been authored by an employee of National Technology & Engineering Solutions of Sandia, LLC, under Contract DE-NA0003525 with the U.S. Department of Energy (DOE).