多项式时间

Few算子和多项式时间概率算法PP的能力

On the power of probabilistic polynomial time and few operator

第二个算法需要花费输入集合的多项式时间倍，此算法有效地计算来自XML关键字的函数依赖最小覆盖的算法。

The second algorithm takes polynomial time in the size of input . This algorithm effectively finds a minimum cover for FDs propagated from XML keys .

NP完全问题多项式时间算法研究

Study on the Polynomial-time Algorithms of NP Complete Problems

本文讨论问题T1的几个多项式时间的可解情形。

Time is * This paper deals with the cases solvable for the problem T1 .

我们证明了：MAX~+（k）中公式的改名问题在多项式时间内可以判定，并给出相应的算法。

The proof is based on the splitting technology and the fact that the complexities of renamings of formulas in MAX ( 1 ) are polynomial time .

一个SNP问题的多项式时间算法

A polynomial algorithm for a SNP problem

本文证明这两种系统可求解著名的NP完全问题，可以在多项式时间内求解给定规模的NP完全问题的所有算例。

This dissertation proved that these two systems can solve all instances of NP-complete problem in a polynomial time .

最后给出了一个求FD集最优覆盖的多项式时间算法。

Finally , a polynomial time algorithm for solving an optimal cover of FD set is given .

这两类算法是在ML算法基础上放松约束条件，将问题转化为可在多项式时间内解决的凸优化问题。

These two algorithms relax the constraints of ML algorithm and transform it into a convex problem which can be efficiently solved with a polynomial time .

网络优化问题是一类特殊的组合优化问题，很多问题找不到求最优解的多项式时间算法，属于NP困难问题；

Network optimization is special problem of combinatorial optimization . Many questions belong to non-determin-istic polynomial problems ( NP ) .

Steiner树作为组播的经典NP问题，无法在多项式时间内找到最优解。

Steiner tree multicast as a classic NP-hard problem cannot find the optimal solution in polynomial time .

由于图的着色问题属于NP完全问题，不可能在多项式时间内得到最优解。

Because graph coloring problem belongs to NP complete problems , it can not get the optimal solution in polynomial time .

阐述了多任务的资源调度问题的形式化定义、复杂性和可近似性难度分析，证明了该问题是NP完全的且是强NP完全的，不存在任何常数近似比的多项式时间近似算法。

It was concluded that the problem is strong NP complete without any approximate algorithms that had constant polynomial time approximate ratio .

最后，利用双层规划的对偶理论，给出求解OEM业务最优策略的一种多项式时间算法。

Finally a polynomial-time algorithm for the optimal strategy of OEM is gotten by using dual theory of bilevel programming .

在考虑子任务间逻辑依赖关系和转移成本的情况下，探讨了针对这类复杂任务结构的服务Agent联盟形成问题，并且提出了一种基于动态规划的多项式时间算法。

We consider the Agent Coalition Formation Problem with logical dependency and transfer cost . And , we propose an algorithm with polynomial time complexity on the basis of Dynamic Planning , to solve this problem .

后者的计算时间复杂性远远低于2N（N为图的顶点数），已接近于多项式时间复杂性。

The computational complexity of the improved algorithm approaches polynomial complexity , much less than 2 N ( N is the vertex number of a graph ) .

例如Shor的算法能在多项式时间内找到一个N位函数的周期。

Shor 's algorithm , for example , is able to find the period of a function of N bits in polynomial time .

SAT问题是NP完全问题，从理论上说，SAT问题不能在多项式时间内解决，它超出了现代计算机的能力。

SAT problem belongs to the NP class , that is , theoretically it can 't be solved in polynomial time and solving it exceeds the capability of modern computer .

通过给出具体的确定型图林机，证明了SBE的可满足性（SAT）问题在多项式时间内可解。

It is proved that the SEE ' satisfiability is solvable in the polynomial time by means of giving a concrete deterministic Turing Machine .

20世纪70年代至今的计算复杂性理论表明，对于NP难度问题可能根本就不存在多项式时间复杂度的求解算法，于是人们使用各种启发式算法求此类问题的近似解。

Investigations from the 1970s to now , show that for NP hard problems , there possibly does not exist an algorithm is of Polynomial time complexity .

车间调度是一类典型的NP-hard问题，已被证明在多项式时间内得不到最优值。

Shop scheduling problem is typically NP-hard , which means that it is impossible to find the global optimum in polynomial complexity .

Shamir多项式时间算法的推广

The Generalization of Shamir Polynomial Time Algorithm

在QoS路由算法研究过程中，形成了三类重要子问题：约束最短路径问题（RSP）；它是NP-完全的，并有许多具有多项式时间和伪多项式时间的启发式求解算法。

A basic problem in QoS routing is the restricted shortest path problem ( RSP ), which is known to be non-polynomial ( NP ) .

本文首先给出了该问题的数学模型，并证明了其是NP-hard问题，因此提出了一个多项式时间的启发式算法。

This dissertation gives a mathematical model of the problem and proves its NP-hardness , and therefore proposes a polynomial time heuristic algorithm .

我们将文献中基于邻域搜索思想的2-OPT操作推广为k，k-交换操作，利用此操作，给出了一个多项式时间近似方案，从而大大改进了文献中的结果。

With new operation , we present a polynomial time approximation scheme for the considered problem , which greatly improves the known result .

可满足性问题是六个基本的NP完全问题之一，其他NP完全问题均可在多项式时间内转换为可满足性问题。

The Satisfiability problem ( SAT ) is one of the six basic NP-complete problems . Other NP-complete problems could be transformed into the Satisfiability problem in polynomial time .

但作业车间调度问题是非常典型的NP-hard问题，迄今为止仍未找到可以精确求得最优解的多项式时间算法。

However , cause the job-shop scheduling problem is a typical NP-hard problem , optimal solutions can still not be precisely obtained by far .

给出了一个多项式时间近似方案（PTAS）。

A polynomial time approximation scheme ( PTAS ) for this problem is presented .

本文提出了无向图（k，m）最优划分的一个近似算法，证明了这是一个产生近似最优解的多项式时间算法。

In this paper we present an approximation algorithm for ( k , m ) optimal partition problem on an undirected graph . We show that this approximation algorithm which produces a near optimal solution runs in polynomial time .

异构无线网络中取得max-min公平带宽分配是一个NP-hard问题，设计了多项式时间算法来获得次优的近似解。

The max-min bandwidth fairness allocation in HWNs is NP-hard problem , so an approximation algorithm of polynomial-time is designed to obtain suboptimal result .