Hans L. Bodlaender , Carla Groenland , Jesper Nederlof , Céline Swennenhuis
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引用次数: 0
摘要
让 XNLP 成为一类参数化问题,即对于某个可计算函数 f,可以在时间 f(k)nO(1) 和空间 f(k)log(n) 内非确定地解决一个参数为 k 的 n 大小实例。我们给出了各种各样的 XNLP-complete(XNLP-complete)问题,如以路径宽度为参数的列表着色和预着色扩展、以机器数量和部分阶宽度为参数的带优先级约束的作业调度、带宽和加权 CNF-可满足性的变体。特别是,这意味着对于所有 t,所有这些问题都是 W[t]-hard 的。
Parameterized problems complete for nondeterministic FPT time and logarithmic space
Let XNLP be the class of parameterized problems such that an instance of size n with parameter k can be solved nondeterministically in time and space (for some computable function f). We give a wide variety of XNLP-complete problems, such as List Coloring and Precoloring Extension with pathwidth as parameter, Scheduling of Jobs with Precedence Constraints, with both number of machines and partial order width as parameter, Bandwidth and variants of Weighted CNF-Satisfiability. In particular, this implies that all these problems are -hard for all t.
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