{"title":"MaxSMT 的局部搜索算法(LIA)","authors":"Xiang He, Bohan Li, Mengyu Zhao, Shaowei Cai","doi":"arxiv-2406.15782","DOIUrl":null,"url":null,"abstract":"MaxSAT modulo theories (MaxSMT) is an important generalization of\nSatisfiability modulo theories (SMT) with various applications. In this paper,\nwe focus on MaxSMT with the background theory of Linear Integer Arithmetic,\ndenoted as MaxSMT(LIA). We design the first local search algorithm for\nMaxSMT(LIA) called PairLS, based on the following novel ideas. A novel operator\ncalled pairwise operator is proposed for integer variables. It extends the\noriginal local search operator by simultaneously operating on two variables,\nenriching the search space. Moreover, a compensation-based picking heuristic is\nproposed to determine and distinguish the pairwise operations. Experiments are\nconducted to evaluate our algorithm on massive benchmarks. The results show\nthat our solver is competitive with state-of-the-art MaxSMT solvers.\nFurthermore, we also apply the pairwise operation to enhance the local search\nalgorithm of SMT, which shows its extensibility.","PeriodicalId":501033,"journal":{"name":"arXiv - CS - Symbolic Computation","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Local Search Algorithm for MaxSMT(LIA)\",\"authors\":\"Xiang He, Bohan Li, Mengyu Zhao, Shaowei Cai\",\"doi\":\"arxiv-2406.15782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MaxSAT modulo theories (MaxSMT) is an important generalization of\\nSatisfiability modulo theories (SMT) with various applications. In this paper,\\nwe focus on MaxSMT with the background theory of Linear Integer Arithmetic,\\ndenoted as MaxSMT(LIA). We design the first local search algorithm for\\nMaxSMT(LIA) called PairLS, based on the following novel ideas. A novel operator\\ncalled pairwise operator is proposed for integer variables. It extends the\\noriginal local search operator by simultaneously operating on two variables,\\nenriching the search space. Moreover, a compensation-based picking heuristic is\\nproposed to determine and distinguish the pairwise operations. Experiments are\\nconducted to evaluate our algorithm on massive benchmarks. The results show\\nthat our solver is competitive with state-of-the-art MaxSMT solvers.\\nFurthermore, we also apply the pairwise operation to enhance the local search\\nalgorithm of SMT, which shows its extensibility.\",\"PeriodicalId\":501033,\"journal\":{\"name\":\"arXiv - CS - Symbolic Computation\",\"volume\":\"2 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Symbolic Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2406.15782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Symbolic Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.15782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MaxSAT modulo theories (MaxSMT) is an important generalization of
Satisfiability modulo theories (SMT) with various applications. In this paper,
we focus on MaxSMT with the background theory of Linear Integer Arithmetic,
denoted as MaxSMT(LIA). We design the first local search algorithm for
MaxSMT(LIA) called PairLS, based on the following novel ideas. A novel operator
called pairwise operator is proposed for integer variables. It extends the
original local search operator by simultaneously operating on two variables,
enriching the search space. Moreover, a compensation-based picking heuristic is
proposed to determine and distinguish the pairwise operations. Experiments are
conducted to evaluate our algorithm on massive benchmarks. The results show
that our solver is competitive with state-of-the-art MaxSMT solvers.
Furthermore, we also apply the pairwise operation to enhance the local search
algorithm of SMT, which shows its extensibility.