Graph Coloring problem (GCP) is an NP hard problem.
图着色问题(GCP)是NP完全问题。
The fill in problem for graphs is a well known NP hard problem.
图的最小填充问题是熟知的NP-困难问题。
Power network planning is a NP hard problem difficult to be solved.
电网规划是一个较难解决的NP难问题。
Automatic test paper generation is a NP hard problem while restrictions exist.
试题库自动组卷问题是一个NP难题。
The connected augmentation of weighted graphs is NP hard problem that has been proved.
加权图的连通扩充问题已被证明是NP完全问题。
Strip layout is the key procedure in progressive die design, it is known as a NP hard problem.
级进模工步排样是级进模设计的核心，理论上属NP完全问题。
Optimization of system reliability is a NP hard problem, and people can not find the precise method for result.
系统可靠性优化已被证明是一个NP完全问题，不存在精确的求解方法。
Attribute reduction of rough sets is an NP hard problem, but there is not a popular efficient algorithm presently.
粗糙集的属性约简是一个NP难的问题，但没有一个目前流行的有效的算法。
Because the planning problem includes integral constrains and nonlinear constrains, it is always a NP hard problem.
此类规划问题包含有大量的整数规划及非线性约束，因而被广泛认为是一类NP难题。
Integer Programming is a famous NP hard problem. This paper presents a new algorithm, in which the method of similar dimidiate is adopted.
整数规划是NP困难的经典问题之一，将传统的二分搜索方法推广应用到整数规划的解空间中，提出一种求解整数规划的新算法。
Absrtact: Task scheduling algorithm has been proved to be a NP hard problem in the dynamic, heterogeneous and complicated grid environment.
摘要：在动态、异构的复杂网格环境中，任务调度算法已被证明是一个NP难问题。
Three dimension packing problem with multi constraints is a complicated combinatorial optimization, and is NP HARD problem. It is difficult to obtain on optimal solution.
多约束条件下的三维装箱问题是一个复杂的组合优化问题，属于NP-HARD问题，其求解是很困难的。
Due to the NP hard problem, it is not realistic to find the optimal decision tree. So researching kinds of heuristic algorithms to induce a decision tree with high accuracy becomes a focus.
由于NP困难，寻找最优的决策树是不现实的，从而探索各种启发式算法去产生一个高精度的决策树变成了这类研究的焦点。
Vehicle scheduling problem with non full load is a fundamental problem of vehicle scheduling problem. Because it is a typical NP hard problem, traditional algorithms usually are not satisfied.
非满载车辆调度问题是车辆调度问题中的一个基本问题，由于它是一个典型的NP难题，传统方法的求解结果往往不能令人满意。
Coloring of conflict graphs has been used in high level synthesis to map operators, values and data transfers onto Shared resources, however, finding a minimum sized coloring is NP hard problem.
高层次综合中通过对冲突围着色方式把操作、变量值、数据传输映射到共享资源中，然而寻找图着色所需的最小颜色数目是个NP难题。
The vehicle-scheduling problem with time window is also a NP-hard problem being more complicated than VSP.
带有时间窗的车辆优化调度问题是比VSP复杂程度更高的NP难题。
In the last, the paper designs and analyses the Graph Theory algorithm and drives a conclusion that the problem of the arranging of curriculum schedule is NP - hard problem.
在文章的最后我们对课表超图的图论算法进行设计与分析，并得出该问题是一个NP难问题。
But it is a NP-Hard problem to get the minimal attribute reduction.
但求取任意问题的最小属性集是一个NP难问题。
The problem of maximizing total weighted satisfaction level for single machine with fuzzy due-date is a NP-hard problem.
单机模糊交货期总加权满意程度最大化问题是一个NP -难问题。
As a combinatorial optimization problem, three dimension packing problem with multi-constraints is NP-HARD problem. It is very difficult to obtain an optimal solution.
作为一类组合优化问题，多约束条件下的三维装载问题属于NP - Hard问题，其求解也是相当困难的。
In complexity theory, set packing problems is an important NP-hard problem, which is used widely in the fields of scheduling and code optimization.
在复杂性理论中，此问题是一类重要的NP难问题，被广泛应用于调度、代码优化和生物信息学等领域。
Finding an optimal scheduling for such an environment is a NP-hard problem, and so heuristic approaches must be used in general to get an optimal approximation solution.
由于在这样的环境中找到一个最优的调度是一个NP难问题，通常运用各种启发式算法来找到近似最优解。
Test set problem is a NP-hard problem with wide applications.
测试集问题是一个有着广泛应用的NP难问题。
It is difficult to solve in large scale because the LRP is a typical NP-hard problem in combinatorial optimization.
由于定位-车辆路线问题是组合优化问题中一个典型的NP难题，大规模时难以精确求解。
It has been proved the computation of minimal reduction and full reduction both is NP-hard problem, in artificial intelligence the common way is to employ heuristic knowledge to reduce.
研究表明，最小约简的计算和全部约简的求算都是NP问题，在人工智能中，解决这类问题的一般方法是利用启发式信息进行约简。
But the RWA in mesh networks is a NP-hard problem which can not be solved optimally with exhaustive search in the endurable time. Hence, we designed a heuristic algorithm to solve it.
而格状网络中的RWA是个NP -难问题，它不可能在有限的时间内通过穷举搜索来获得其优化解，为此我们设计了一个启发性算法以解决这个问题。
In this paper we propose there efficient arithmetic-weal search, much space search and overall situation search for sowing NP-hard problem.
提出三种有效的快速算法——局部搜索、多空间搜索和全局搜索来解决NP难度问题。
Recent studies show that the problem is NP-hard.
最近的研究成果表明这一问题是NP难问题。
Recent studies show that the problem is NP-hard.
最近的研究成果表明这一问题是NP难问题。
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