Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function
February 15, 2017 Β· Declared Dead Β· π International Joint Conference on Artificial Intelligence
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Authors
Yiyuan Wang, Shaowei Cai, Minghao Yin
arXiv ID
1702.04594
Category
cs.AI: Artificial Intelligence
Citations
59
Venue
International Joint Conference on Artificial Intelligence
Last Checked
3 months ago
Abstract
The Minimum Weight Dominating Set (MWDS) problem is an important generalization of the Minimum Dominating Set (MDS) problem with extensive applications. This paper proposes a new local search algorithm for the MWDS problem, which is based on two new ideas. The first idea is a heuristic called two-level configuration checking (CC2), which is a new variant of a recent powerful configuration checking strategy (CC) for effectively avoiding the recent search paths. The second idea is a novel scoring function based on the frequency of being uncovered of vertices. Our algorithm is called CC2FS, according to the names of the two ideas. The experimental results show that, CC2FS performs much better than some state-of-the-art algorithms in terms of solution quality on a broad range of MWDS benchmarks.
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