期刊文献+

约束满足问题求解的符号OBDD桶消元算法 被引量:4

OBDD-based Bucket Elimination Algorithm for Constraint Satisfaction Problem
在线阅读 下载PDF
导出
摘要 桶消元算法是求解约束满足问题的一种典型推理方法。针对桶消元算法面临的状态空间爆炸问题,将有序二叉决策图(OBDD)技术与该算法结合起来,给出了约束满足问题的一种求解算法。通过对约束满足问题中变量和域值的编码,将CSP问题转化为命题可满足性问题,给出了约束满足问题的OBDD表示方法;基于桶消元的算法思想,在约束满足问题的OBDD表示的基础上,利用OBDD的"与"操作和"量化"操作等,避免了传统算法中状态的显式枚举,隐式地实现了对CSP的求解。对大量随机生成的测试用例进行了实验分析,结果表明提出的符号算法明显优于桶消元法和符号直接求解法。 Bucket-elimination algorithm is a typical reasoning method for the constraint satisfaction problem(CSP).Aiming at the state explosion problem of bucket-elimination algorithm,ordered binary decision diagram(OBDD) technique was combined with bucket-elimination algorithm,and a symbolic OBDD-based algorithm for CSP was proposed.By encoding each variable and each value in the domain as binary variables,CSP was encoded as a propositional satisfiability(SAT) problem,and then CSP was formulated symbolically by OBDD.Based on the ideas of bucket-elimination algorithm and the symbolic OBDD representation of CSP,the CSP was solved implicitly by the AND operator and the EXIST operator of OBDD,so that the explicit enumeration of states in traditional algorithms was avoided.The simulation results show that the symbolic algorithm is more efficient than both the bucket-elimination algorithm and the direct algorithm based on OBDD.
出处 《计算机科学》 CSCD 北大核心 2011年第7期200-202,219,共4页 Computer Science
基金 国家自然科学基金(60963010 60903079 61063002) 广西自然科学基金重点项目(0832006Z)资助
关键词 约束满足问题 符号算法 桶消元 有序二叉决策图(OBDD) Constraint satisfaction problem Symbolic algorithm Bucket elimination Ordered binary decision diagram(OBDD)
  • 相关文献

参考文献11

  • 1Sadeh N, Sycara K, Xiong Y. Bachtracking techniques for the job shop scheduling constraint satisfaction problem [J]. Artificial Intelligence, 1995,76 (1/2) : 455-480.
  • 2伍丽华,陈蔼洋,姜云飞.规划问题编码为约束可满足问题的研究[J].计算机科学,2006,33(8):187-189. 被引量:3
  • 3Pham D N, Thornton J, Sattar A. Modelling and Solving tempo- ral reasoning as propositional satisfiability [J]. Artificial Intelli- gence, 2008,172(15) : 1725-1782.
  • 4Miguel I, Shen Q. Solution Techniques for Constraint Satisfac- tion Problems: Foundations [J]. Artificial Intelligence Review, 2001,15 (4) : 243-267.
  • 5Dechter R. Bucket Eliminatiom A Unifying Framework for Rea- soning[J]. Artificial Intelligence, 1999,113 : 41-85.
  • 6Bryant R E. Symbolic Boolean Manipulation with Ordered Binary Decision Diagrams [J]. ACM Computer Survey, 1992,24 ( 3 ) : 293-318.
  • 7Burch J, Clarke E, Memillan K, et al. Symbolic Model Checking: 10^20 States and Beyond[J]. Information and Computation, 1998, 98(2):142-170.
  • 8Hachtel G D, Somenzi F. A Symbolic Algorithm for Maximum Flow in 0-1 Networks [J]. Formal Methods in System Design, 1997,10(2/3) : 207-219.
  • 9Pan G, Vardi M Y. Symbolic Techniques in Satisfiability Solving [J]. Journal of Automated Reasoning, 2005,35 (1-3) :25-50.
  • 10Walsh T. SAT v CSP [C] // Proceeding of the 6th international Conference on Principles and Practice of Constraint Program- ming. 2000,1894 : 441-456.

二级参考文献24

  • 1吴康恒,姜云飞.基于模型检测的领域约束规划[J].软件学报,2004,15(11):1629-1640. 被引量:17
  • 2徐周波,古天龙,赵岭忠.网络最大流问题的一种新的符号ADD求解算法[J].通信学报,2005,26(2):1-8. 被引量:15
  • 3de Fazio T L,Whitney D E.Simplified generation of all mechanical assembly sequences[J].IEEE Journal of Robotics and Automation,1987,RA-3(6):640-658.
  • 4de Mello L S H,Sanderson A C.A Correct and complete algorithm for the generation of mechanical assembly sequences[J].IEEE Transactions on Robotics and Automation,1991,7(2):228-240.
  • 5Bryant R E.Symbolic Boolean manipulation with ordered binary decision diagrams[J].ACM Computing Surverys,1992,24(3):293-318.
  • 6Burch J R,Clarke E M,Mcmillan K L,et al.Symbolic model checking:1020 states and beyond[J].Information and Computation,1992,98(2):143-170.
  • 7Gu Tianlong,Liu Huadong.The symbolic OBDD scheme for generating mechanical assembly sequences[J].Formal Methods in System Design,2008,33(1/3):29-44.
  • 8Purvis L S.Intelligent design problem solving using case based and constraint based techniques[D].Connecticut:University of Connecticut,1995.
  • 9Minato S,Ishiua N,Yajima S.Shared binary decision diagram with attributed edges for efficient Boolean function manipulation[C] //Proceedings of the 27th ACM/IEEE Design Automation Conference,New York,1990:52-57.
  • 10Brailsford S C,Potts C N,Smith B M.Constraint satisfaction problems:algorithms and applications[J].European Journal of Operational Research,1999,119(3):557-581.

共引文献9

同被引文献23

  • 1古天龙,杨志飞.基于有序二叉决策图的装配序列符号表示方法[J].计算机辅助设计与图形学学报,2007,19(10):1315-1320. 被引量:4
  • 2Akers S B.Binary decision diagrams[J].IEEE Transactions on Computer,1978,27(6):509-516.
  • 3Bryant R E.Graph based algorithms for Boolean function manipulation[J].IEEE Transactions on Computer,1986,35(8):677-691.
  • 4Wei Qianjin,Gu Tianlong.Symbolic representation for rough set attribute reduction using ordered binary decision diagrams[J].Journal of Software,2011,6(6):977-984.
  • 5Yang Liu,Manadhata P K,Horne W G,et al.Fast submatch extraction using OBDDs[R].[S.l.]:HP Laboratories,2012.
  • 6Wang Chong,Vittal V,Sun K.OBDD-based sectionalizing strategies for parallel power system restoration[J].IEEE Transactions on Power Systems,2011,26(3):1426-1433.
  • 7Somenzi F.CUDD:CU decision diagram package release2.4.1[EB/OL].[2013-09-11].http://vlsi.Colorado.edu/fabio/CUDD/cuddIntro.html.
  • 8Jackson P.BDD operations[EB/OL].[2013-12-21].www.inf.ed.ac.uk/teaching/courses/ar/slides/bdd-ops.pdf.
  • 9Kanoh H, Hasegawa K, Matsumoto M, et al. Solving constraint satisfaction problems by a genetic algorithm adopting viral infection[C]//Intelligence and Systems, IEEE International Joint Symposia, 1996 : 67-73.
  • 10Mu Shengjing,Su Hongye,Mao Weijie,et al. A new ge- netic algorithm to handle the constrained optimization problem[C]//Proceedings of the 41st IEEE Conference on Decision and Control, 2002 : 739-740.

引证文献4

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部