Separate, measure and conquer: faster polynomial-space algorithms for Max 2-CSP and counting dominating sets

Gaspers, S. & Sorkin, G. B.ORCID logo (2017). Separate, measure and conquer: faster polynomial-space algorithms for Max 2-CSP and counting dominating sets. ACM Transactions on Algorithms, 13(4), 1-36. https://doi.org/10.1145/3111499
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We show a method resulting in the improvement of several polynomial-space, exponential-time algorithms. The method capitalizes on the existence of small balanced separators for sparse graphs, which can be exploited for branching to disconnect an instance into independent components. For this algorithm design paradigm, the challenge to date has been to obtain improvements in worst-case analyses of algorithms, compared with algorithms that are analyzed with advanced methods, notably Measure and Conquer. Our contribution is the design of a general method to integrate the advantage from the separator-branching into Measure and Conquer, for a more precise and improved running time analysis

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