[1] 陈稳. 基于DPLL的SAT算法的研究及应用[D]. 成都:电子科技大学, 2011.
[2] KAUTZ H, SELMAN B. The state of SAT[J]. Discrete Applied Mathematics, 2007,155(12):1514-1524.
[3] 张健. 逻辑公式的可满足性判定[M]. 北京:科学出版社, 2000: 8-20.
[4] MARQUES-SILVA J P, SAKALLAH K A. GRASP: A new search algorithm for satisfiability[C]// International Conference on Computer Aided Design. 1996:220-227.
[5] MARQUES-SILVA J P, SAKALLAH K. Invited tutorial: Boolean satisfiability algorithms and applications in electronic design automation[C]// Proceedings of the 12th International Conference on Computer Aided Verification. 2000:3.
[6]〖KG-*5〗 MOSKEWICZ M W, MADIGAN C F, ZHAO Y, et al. Chaff: Engineering an efficient SAT solver [C]// Proceedings of the 38th Annual Design Automation Conference. 2001:530-535.
[7] GOLDBERG E, NOVIKOV Y. BerkMin: A fast and robust SAT-solver[J]. Discrete Applied Mathematics, 2007,155(12):1549-1561.
[8] HUANG J. The effect of restarts on the efficiency of clause learning[C]// Proceedings of the 20th International Joint Conference on Artificial Intelligence. 2007:2318-2323.
[9] MARQUES-SILVA J P, LYNCE I, MALIK S. Conflict-driven clause learning SAT solvers[J]. Frontiers in Artificial Intelligence & Applications, 2009,185(1):131-153.
[10]MAHAJAN Y S, FU Z, MALIK S. Zchaff2004: An efficient SAT solver[C]// International Conference on Theory and Applications of Satisfiability Testing. 2004:360-375.
[11]EN N, SRENSSON N. An extensible SAT-solver[C]// International Conference on Theory and Applications of Satisfiability Testing. 2003:502-518.
[12]AUDEMARD G, SIMON L. Glucose: A solver that predicts learnt clauses quality[C]// Proceedings of SAT Competition. 2009:7-8.
[13]BIERE A. Lingeling, Plingeling, PicoSAT and PrecoSAT at SAT Race 2010[R]. FMV Report Series Technical Report, Institute for Formal Models and Verification, Johannes Kepler University, 2010.
[14]BIERE A. Lingeling, Plingeling and Treengeling entering the SAT competition 2013[C]// Proceedings of SAT Com-petition. 2013:51-52.
[15]常文静,徐扬,吴贯锋. 基于演绎长度的学习子句删除策略[J]. 计算机工程与应用, 2018,54(16):30-36.
[16]AUDEMARD G, SIMON L. Predicting learnt clauses quality in modern SAT solvers[C]// Proceedings of the 21st International Joint Conference on Artificial Intelligence. 2009:399-404.
[17]ANSTEGUI C, GIRLDEZ-CRU J, LEVY J, et al. Using community structure to detect relevant learnt clauses[C]// International Conference on Theory & Applications of Satisfiability Testing. 2015:238-254.
[18]GOLDBERG E, NOVIKOV Y. BerkMin: A fast and robust SAT-solver[C]// Design, Automation, and Test in Europe. 2002:465-478.
[19]杜忠和. 基于CDCL结构的SAT问题优化策略的研究[D]. 成都:西南交通大学, 2018.
[20]GUO L, JABBOUR S, LONLAC J, et al. Diversification by clauses deletion strategies in portfolio parallel SAT solving[C]// Proceedings of IEEE the 26th International Conference on Tools with Artificial Intelligence. 2014:701-708.
[21]NABESHIMA H, INOUE K. Coverage-based clause reduction heuristics for CDCL solvers[C]// Proceedings of the 20th International Conference on Theory and Applications of Satisfiability Testing. 2017:136-144.
[22]JABBOUR S, LONLAC J, SAIS L, et al. Revisiting the learned clauses database reduction strategies[J]. Computer Science, 2014, arXiv:1402.1956. |