Local search heuristics for Quadratic Unconstrained Binary Optimization (QUBO)

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 ef...

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Veröffentlicht in:Journal of heuristics Jg. 13; H. 2; S. 99 - 132
Hauptverfasser: Boros, Endre, Hammer, Peter L., Tavares, Gabriel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer Nature B.V 01.04.2007
Schlagworte:
Algorithms
Boolean
Heuristic
Integer programming
Mathematical models
Optimization
Studies
Variables
ISSN:1381-1231, 1572-9397
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Zusammenfassung: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. [PUBLICATION ABSTRACT]
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:1381-1231
1572-9397
DOI:10.1007/s10732-007-9009-3