Building an iterative heuristic solver for a quantum annealer

Gili Rosenberg (), Mohammad Vazifeh (), Brad Woods () and Eldad Haber ()
Additional contact information
Gili Rosenberg: 1QB Information Technologies (1QBit)
Mohammad Vazifeh: 1QB Information Technologies (1QBit)
Brad Woods: 1QB Information Technologies (1QBit)
Eldad Haber: University of British Columbia

Computational Optimization and Applications, 2016, vol. 65, issue 3, No 13, 845-869

Abstract: Abstract A quantum annealer heuristically minimizes quadratic unconstrained binary optimization (QUBO) problems, but is limited by the physical hardware in the size and density of the problems it can handle. We have developed a meta-heuristic solver that utilizes D-Wave Systems’ quantum annealer (or any other QUBO problem optimizer) to solve larger or denser problems, by iteratively solving subproblems, while keeping the rest of the variables fixed. We present our algorithm, several variants, and the results for the optimization of standard QUBO problem instances from OR-Library of sizes 500 and 2500 as well as the Palubeckis instances of sizes 3000–7000. For practical use of the solver, we show the dependence of the time to best solution on the desired gap to the best known solution. In addition, we study the dependence of the gap and the time to best solution on the size of the problems solved by the underlying optimizer. Our results were obtained by simulation, using a tabu 1-opt solver, due to the huge number of runs required and limited quantum annealer time availability.

Keywords: Quantum annealing; Quadratic unconstrained binary optimization; Combinatoric optimization; k-opt; Local search; Iterative heuristic solver (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10589-016-9844-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:coopap:v:65:y:2016:i:3:d:10.1007_s10589-016-9844-y

Ordering information: This journal article can be ordered from
http://www.springer.com/math/journal/10589

DOI: 10.1007/s10589-016-9844-y

Access Statistics for this article

Computational Optimization and Applications is currently edited by William W. Hager

More articles in Computational Optimization and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().