Incremental symmetry breaking constraints for graph search problems

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Abstract

This paper introduces incremental symmetry breaking constraints for graph search problems which are complete and compact. We show that these constraints can be computed incrementally: A symmetry breaking constraint for order n graphs can be extended to one for order n + 1 graphs. Moreover, these constraints induce a special property on their canonical solutions: An order n canonical graph contains a canonical subgraph on the first k vertices for every 1 ≤ k ≤ n. This facilitates a “generate and extend” paradigm for parallel graph search problem solving: To solve a graph search problem ϕ on order n graphs, first generate the canonical graphs of some order k < n. Then, compute canonical solutions for ϕ by extending, in parallel, each canonical order k graph together with suitable symmetry breaking constraints. The contribution is that the proposed symmetry breaking constraints enable us to extend the order k canonical graphs to order n canonical solutions. We demonstrate our approach through its application on two hard graph search problems.

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APA

Itzhakov, A., & Codish, M. (2020). Incremental symmetry breaking constraints for graph search problems. In AAAI 2020 - 34th AAAI Conference on Artificial Intelligence (pp. 1536–1543). AAAI press. https://doi.org/10.1609/aaai.v34i02.5513

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