Journal of Heuristics

, Volume 13, Issue 2, pp 99–132

Local search heuristics for Quadratic Unconstrained Binary Optimization (QUBO)


DOI: 10.1007/s10732-007-9009-3

Cite this article as:
Boros, E., Hammer, P.L. & Tavares, G. J Heuristics (2007) 13: 99. doi:10.1007/s10732-007-9009-3


We present a family of local-search-based heuristics for Quadratic Unconstrained Binary Optimization (QUBO), all of which start with a (possibly fractional) initial point, sequentially improving its quality by rounding or switching the value of one variable, until arriving to a local optimum. The effects of various parameters on the efficiency of these methods are analyzed through computational experiments carried out on thousands of randomly generated problems having 20 to 2500 variables. Tested on numerous benchmark problems, the performance of the most competitive variant (ACSIOM) was shown to compare favorably with that of other published procedures.


Integer programmingLocal optimizationQuadratic unconstrained binary optimizationQuadratic pseudo-Boolean functionsHeuristics

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Endre Boros
    • 1
  • Peter L. Hammer
    • 1
  • Gabriel Tavares
    • 1
  1. 1.RUTCORRutgers UniversityPiscatawayUSA