{"title":"CHAMP: A multipass algorithm for Max Sat based on saver variables","authors":"Daniel Berend , Shahar Golan , Yochai Twitto","doi":"10.1016/j.disopt.2023.100760","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we introduce the concept of saver variables in Max Sat and demonstrate their contribution to the performance of solvers for this problem. We present two types of saver variables: high-rank savers and consensual savers. We show how to incorporate them in various ways into an iterated algorithm, CHAMP, for Max Sat. We conduct an extensive empirical evaluation on two collections of instances — instances from a past Max Sat competition and random instances. It turns out that, by using savers, the number of unsatisfied clauses may be reduced by more than 70% in some families. Moreover, a refined version CHAMP＋ of CHAMP improves the results even further. We show that by combining CHAMP＋ with CCLS, a state-of-the-art solver, we obtain better solutions for many Max Sat instances.</p></div>","PeriodicalId":50571,"journal":{"name":"Discrete Optimization","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discrete Optimization","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1572528623000026","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
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Abstract
In this paper, we introduce the concept of saver variables in Max Sat and demonstrate their contribution to the performance of solvers for this problem. We present two types of saver variables: high-rank savers and consensual savers. We show how to incorporate them in various ways into an iterated algorithm, CHAMP, for Max Sat. We conduct an extensive empirical evaluation on two collections of instances — instances from a past Max Sat competition and random instances. It turns out that, by using savers, the number of unsatisfied clauses may be reduced by more than 70% in some families. Moreover, a refined version CHAMP＋ of CHAMP improves the results even further. We show that by combining CHAMP＋ with CCLS, a state-of-the-art solver, we obtain better solutions for many Max Sat instances.
期刊介绍：
Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.
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