论文标题
提高约束满意度算法效率的效率
Improving Constraint Satisfaction Algorithm Efficiency for the AllDifferent Constraint
论文作者
论文摘要
研究了组合问题为约束满意度问题（CSP）。示例表明，当同时应用于原始问题及其互补问题时，为原始CSP设计的任何算法以及涉及alldiverent限制的算法至少具有相同的功效。引入了用于将CSP转换为其互补问题的1对1映射（也是CSP）。概述了此“双CSP”方法及其应用。对几个随机问题实例的分析表明，与CSP的标准方法相比，该方法对可变域的降低的好处。提出了对这种双CSP方法的候选者的候选者，对其他约束以及使用混合算法的使用扩展。
Combinatorial problems stated as Constraint Satisfaction Problems (CSP) are examined. It is shown by example that any algorithm designed for the original CSP, and involving the AllDifferent constraint, has at least the same level of efficacy when simultaneously applied to both the original and its complementary problem. The 1-to-1 mapping employed to transform a CSP to its complementary problem, which is also a CSP, is introduced. This "Dual CSP" method and its application are outlined. The analysis of several random problem instances demonstrate the benefits of this method for variable domain reduction compared to the standard approach to CSP. Extensions to additional constraints other than AllDifferent, as well as the use of hybrid algorithms, are proposed as candidates for this Dual CSP method.
