This algorithm can be extended to solve other NPC problem, such as TSP problem.
这个量子算法可以推广解决其它NPC问题，如旅行售货员问题等。
The question of unmanned spy plane's cruise is TSP problem, regardless of other constraints.
无人侦察机的巡航问题，如果不考虑其它约束条件，实际上是一个TSP问题。
Theoretically speaking, the enumeration not only can solve TSP problem but also can get the best answer.
从理论上讲，使用穷举法不但可以求解tsp问题，而且还可以求出该问题的最优解。
The problem is equivalent to non-symmetric TSP problem, which can be solved using some heuristic algorithm.
该问题等价于非对称的TSP问题，进而可以用相应的启发式算法求解。
Finally, the paper presents DNA molecular algorithms and living examples of TSP problem based on sticker model.
最后给出了基于粘贴系统模型的TSP问题的DNA分子算法和应用实例。
To overcome the shortage, this thesis proposes a method for test application time reduction based on TSP problem.
为了克服这一缺陷，本文提出了一种基于TSP问题降低测试应用时间的方法。
The TSP problem is solved by designing an auxiliary square window and utilizing a "quadrilateral diagonal exchanging" technique.
思路是设计一个矩形辅助窗口，并利用“四边形对角线交换”技术来获得简单多边形的三角剖分。
The TSP problem is considered as classical optimization grouping problem, which is widely used in practice, but it is real a difficult NP problem.
旅行商问题作为经典的组合优化问题，实际中的应用非常广泛，但它却是一个NP完全问题。
The question of flight path programming is TSP problem, regardless of other constraints. There are no effective real time algorithms of TSP problem at present.
无约束的航路规划问题，实际上是一个TSP问题，目前还没有求解TSP问题的比较有效的实时算法。
Procedures of the 48 cities TSP problem (document coordinates corresponding to the city 48. TXT) to calculate the optimal solution of the path and road map are as follows.
程序对48个城市的TSP问题(城市坐标文件对应于48. txt)进行计算，求解路径和最优路径图如下。
Immune algorithm has been successful in many fields, such as virus removal and invasive monitoring, function optimization, TSP problem, data analysis and mining, fault diagnosis.
免疫算法已在很多领域得到了成功的应用，如病毒清除和入侵监控、函数优化、TSP问题、数据分析和挖掘、故障诊断等。
Based on the immune principles, this paper at first analyse the immune algorithm by solving TSP problem which improves the ability of population and increase the holistic performance.
本文利用免疫的有关概念和理论，先对免疫算法性能做分析，设计一个免疫算法求解tsp问题，验证基于免疫的算法有利于整体的相对稳定和性能的提高。
GENIUS algorithm is used to solve TSP problem in this algorithm. Through this processing, not only better solution can be got, but also the likelihood of local optimal be reduced by perturbing sol...
采用GENIUS算法处理其中的TSP问题，不仅能产生较好的解，而且通过对解的周期性的扰动，进一步减少求解陷于局部优化的可能性。
At first, it can support many kind of TSP (include TSP, ATSP and HCP), and can find the best tour of TSPLIB's majority problems in little time (the largest problem has a dimension of 7397 points).
首先，它广泛支持TSPLIB的TSP、ATSP、HCP类问题，对TSPLIB中大部分问题都在较短时间内求出了最优解，包括7397点的TSP问题。
By choosing appropriate operators and parameters, genetic algorithms (GA) can solve the traveling salesman problem (TSP) effectively.
通过选择合适的算子和参数，遗传算法(GA)可以有效求解旅行商问题(tsp)。
As an essential question of the intelligent distribution system, route optimization has many problem-solving models, the most typical one is Traveling Salesman problem (short for TSP).
路径优化是物流配送中智能调度系统的核心问题，其中最典型的问题模型就是旅行商问题即TSP问题。
Second, we apply all of them to 10-city travelling salesman problem (TSP), respectively.
其次将四种方法分别应用于10个城市的旅行推销商问题。
Because TSP is known to be a NP - complete problem in theory, it is too difficult to be solved with traditional optimal methods.
由于TSP问题在理论上属于NP完备问题，很难用一般的算法求解。
The evolutionary algorithm using inver-over operator for the traveling salesman problem(TSP) has great ascendancy, because its ability in global searching for optimal individual is powerful.
使用逆转算子求解TSP的演化算法具有很强全局搜索能力，在求解TSP问题中显示了巨大的优势。
The paper based on the idea of K-OPT Algorithm for TSP, present a swap algorithm for the one-dimensional cutting-stock problem.
根据旅行商问题（TSP）的邻域搜索算法的思想，提出了型材下料问题的一种优化算法。
This article proposes a modified algorithm for solving the travelling salesman problem (TSP) by neural network.
本文提出用神经网络解旅行商问题(tsp)的改进算法。
Therefore propose an effective solution to the problem of the TSP algorithms have a higher theoretical and practical value.
因此提出一种有效地解决TSP问题的算法有着较高的理论意义和实际应用价值。
TSP is a combinational optimization problem which has wide application background and important theory value, and it belongs to classical NP problem.
TSP问题是一个具有广泛的应用背景和重要理论价值的组合优化问题，属于典型的NP问题。
Traveling salesman problem(TSP) and nonlinear equations are two kinds of important problems with widely applications.
旅行商问题（TSP）和非线性方程组都是具有广泛的应用背景的重要问题。
Then Traveling Salesman Problem is described and its mathematics model is provided. Some correlative algorithms are introduced and their capability of solving TSP is compared.
随后叙述了TSP的一般提法，描述了其数学模型，综合介绍了关于解决TSP的相关算法，并做了性能比较。
Solving Traveling Salesman problem (TSP) is an important problem in Genetic Algorithm's Application, it is an optimization problem of the TSP path encoding in essence.
求解tsp问题是遗传算法应用的一个重要领域，其本质是TSP问题中巡回路径编码串的组合最优化问题。
The Film Deliverer Problem(FDP), a new problem in the combination optimization is much more complicated than the Traveling Salesman Problem(TSP).
影片递送问题（简称FDP）是组合优化的一个新问题，它比旅行商问题（简称TSP）复杂得多。
The Film Deliverer Problem(FDP), a new problem in the combination optimization is much more complicated than the Traveling Salesman Problem(TSP).
影片递送问题（简称FDP）是组合优化的一个新问题，它比旅行商问题（简称TSP）复杂得多。
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