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  • Weight Redistribution for Unweighted MAX-SAT

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    49557_1.pdf (183.9Kb)
    Author(s)
    Ishtaiwi, Abdelraouf
    Thornton, John
    Sattar, Abdul
    Griffith University Author(s)
    Sattar, Abdul
    Year published
    2007
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    Abstract
    Many real-world problems are over-constrained and require search techniques adapted to optimising cost functions rather than search- ing for consistency. This makes the MAX-SAT problem an important area of research for the satisility (SAT) community. In this study we perform an empirical analysis of several of the best performing SAT local search techniques in the domain of unweighted MAX-SAT. In particular, we test two of the most recently developed SAT clause weight redistri- bution algorithms, DDFW and DDFW+, against three more well-known techniques (RSAPS, AdaptNovelty+ and PAWS). Based on an empir- ical study ...
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    Many real-world problems are over-constrained and require search techniques adapted to optimising cost functions rather than search- ing for consistency. This makes the MAX-SAT problem an important area of research for the satisility (SAT) community. In this study we perform an empirical analysis of several of the best performing SAT local search techniques in the domain of unweighted MAX-SAT. In particular, we test two of the most recently developed SAT clause weight redistri- bution algorithms, DDFW and DDFW+, against three more well-known techniques (RSAPS, AdaptNovelty+ and PAWS). Based on an empir- ical study across a range of previously studied problems we conclude that DDFW is the most promising algorithm in terms of robust average performance.
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    Conference Title
    AI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS
    Volume
    4830
    DOI
    https://doi.org/10.1007/978-3-540-76928-6_76
    Copyright Statement
    © 2007 Springer. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
    Publication URI
    http://hdl.handle.net/10072/18346
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    • Conference outputs

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