Variable ordering for decision diagrams: A portfolio approach

Relaxed decision diagrams have been successfully applied to solve combinatorial optimization problems, but their performance is known to strongly depend on the variable ordering. We propose a portfolio approach to selecting the best ordering among a set of alternatives. We consider several different...

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Bibliographic Details
Published in:	Constraints : an international journal 2022-04, Vol.27 (1-2), p.116-133
Main Authors:	Karahalios, Anthony, van Hoeve, Willem-Jan
Format:	Article
Language:	eng
Subjects:	Algorithms Artificial Intelligence Combinatorial analysis Computer Science Graph coloring Operations Research/Decision Theory Optimization Prediction models
Online Access:	Get full text
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Summary:	Relaxed decision diagrams have been successfully applied to solve combinatorial optimization problems, but their performance is known to strongly depend on the variable ordering. We propose a portfolio approach to selecting the best ordering among a set of alternatives. We consider several different portfolio mechanisms: a static uniform time-sharing portfolio, an offline predictive model of the single best algorithm using classifiers, a low-knowledge algorithm selection, and a dynamic online time allocator. As a case study, we compare and contrast their performance on the graph coloring problem. We find that on this problem domain, the dynamic online time allocator provides the best overall performance.
ISSN:	1383-7133 1572-9354