Quantum Information Processing

, Volume 14, Issue 1, pp 1–36 | Cite as

A case study in programming a quantum annealer for hard operational planning problems

  • Eleanor G. Rieffel
  • Davide Venturelli
  • Bryan O’Gorman
  • Minh B. Do
  • Elicia M. Prystay
  • Vadim N. Smelyanskiy


We report on a case study in programming an early quantum annealer to attack optimization problems related to operational planning. While a number of studies have looked at the performance of quantum annealers on problems native to their architecture, and others have examined performance of select problems stemming from an application area, ours is one of the first studies of a quantum annealer’s performance on parametrized families of hard problems from a practical domain. We explore two different general mappings of planning problems to quadratic unconstrained binary optimization (QUBO) problems, and apply them to two parametrized families of planning problems, navigation-type and scheduling-type. We also examine two more compact, but problem-type specific, mappings to QUBO, one for the navigation-type planning problems and one for the scheduling-type planning problems. We study embedding properties and parameter setting and examine their effect on the efficiency with which the quantum annealer solves these problems. From these results, we derive insights useful for the programming and design of future quantum annealers: problem choice, the mapping used, the properties of the embedding, and the annealing profile all matter, each significantly affecting the performance.


Quantum computation Quantum annealing keyword  Operational planning 



The authors are grateful to Jeremy Frank, Alejandro Perdomo-Ortiz, Sergey Knysh, Itay Hen, Ross Beyer, and Chris Henze for helpful discussions, and to D-Wave for technical support and for discussions related to the calibration issue and our results before and after. This work was supported in part by the Office of the Director of National Intelligence (ODNI), the Intelligence Advanced Research Projects Activity (IARPA), via IAA 145483; by the AFRL Information Directorate under grant F4HBKC4162G001. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, AFRL, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purpose notwithstanding any copyright annotation thereon. The authors also would like to acknowledge support from the NASA Advanced Exploration Systems program and NASA Ames Research Center.


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Copyright information

© Springer Science+Business Media New York (outside the USA)  2014

Authors and Affiliations

  • Eleanor G. Rieffel
    • 1
  • Davide Venturelli
    • 1
  • Bryan O’Gorman
    • 1
  • Minh B. Do
    • 1
  • Elicia M. Prystay
    • 1
  • Vadim N. Smelyanskiy
    • 1
  1. 1.NASA Ames Research CenterMoffett FieldUSA

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