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[Static controlDisjoint_Set_Forest

Description: 算法——分离集合的实现-algorithm-- the realization of separation pool
Platform: | Size: 2210816 | Author: zeng | Hits:

[ELanguageredundantpaths

Description: c pgm to find redundant paths in a graph.Many fault-tolerant network algorithms rely on an underlying assumption that there are possibly distinct network paths between a source-destination pair. Given a directed graph as input, write a program that uses depth-first search to determine all such paths. Note that, these paths are not vertex-disjoint i.e., the vertices may repeat but they are all edge-disjoint i.e., no two paths have the same edges. The input is the adjacency matrix of a directed acyclic graph and a pair(s) of source and destination vertices and the output should be the number of such disjoint paths and the paths themselves on separate lines. In case of multiple paths the output should be in order of paths with minimum vertices first. In case of tie the vertex number should be taken in consideration for ordering.
Platform: | Size: 2048 | Author: jazz | Hits:

[Othermultistage

Description: 多段图G=(V,E)是一个有向图。它具有如下特征:图中的节点被划分成k>=2个不相交的集合Vi,1<=i<=k,其中V1 与Vk 分别只有一个结点s(源点)和t(汇点)。图中所有的边<u,v> 均具有如下性质:若 ,则 ,1<=i<k-1,且每条边<u,v>均附有成本c<u,v>。从s到t的一条路径成本是这条路径上边的成本和。多段图问题是求s到t的最小成本路径。每个集合 定义图中的一段。由于E得约束,每条从s到t的路径都是从第1段开始,在第k段终止。-Multi-stage graph G = (V, E) is a directed graph. It has the following characteristics: graph node is divided into k> = 2 disjoint sets Vi, 1 < = i < = k, where V1 and Vk are only one node s (source) and t (Meeting Point ). Figure in all of the edges <u,v> All have the following property: If, then, 1 < = i <k-1,且每条边<u,v> Comes with costs c <u,v> . From s to t, the cost of a path is the path on top of costs and. Multistage Graph Problem is seeking a minimum cost s to t path. Defined by a set figure for each section. Since E was bound, and each path from s to t are from the beginning of paragraph 1, paragraph k in the first end.
Platform: | Size: 2048 | Author: jory | Hits:

[Data structsKruskal

Description: 编程实现Kruskal算法,生成最小代价生成树,其中利用最小堆算法实现。 (随机生成n个点,且随机生成k条边,形成连通图) 根据输入的顶点数的不同,分析时间复杂度。-Implement Kruskal’s algorithm based on min-heap and disjoint set data structure for constructing a minimum cost spanning tree. Generate weighted undirected complete graph for given size n according to the following approach: 1) Randomly generate n points (x,y) on a plane 2) Randomly generate k pairs of points as edges of the graph. 3) The weight of an edge of the graph is defined as the the Euclidean distance between two endpoints of the edge.
Platform: | Size: 2048 | Author: 许许 | Hits:

[Data structsPrim

Description: 编程实现Prim算法,基于最小堆数据结构,生成最小代价生成树。 (其中随机生成点和边,形成连通图) 根据输入的顶点数的不同,分析时间复杂度。-Implement Prim’s algorithms based on min-heap and disjoint set data structure for constructing a minimum cost spanning tree. Generate weighted undirected complete graph for given size n according to the following approach: 1) Randomly generate n points ( ) on a plane 2) Randomly generate k pairs of points as edges of the graph. 3) The weight of an edge of the graph is defined as the the Euclidean distance between two endpoints of the edge.
Platform: | Size: 2048 | Author: 许许 | Hits:

[Data structscut-the-minimum-cut-problem

Description: cut 最小割问题 网络G=(V,E)的割cut(S,T)是将G的顶点集V划分为2个不相交的子集S和T,使s Î S , t Î T ,且cut(S,T) = {(u,v)Î E | u Î S,vÎ T}。设每条边(u,v)的边权为a(u,v),则割 cut(S,T)的权值为cut(S,T)中所有边权之和。最小割问题要求网络G 的权值最小的割。-cut the minimum cut problem network G = (V, E) of the cut cut (S, T) is the vertex set V of G into two disjoint subsets S and T, so that s Î S, t Î T, and cut ( S, T) = {(u, v) Î E | u Î S, vÎ T}. Let each edge (u, v) the right side is a (u, v), then cut cut (S, T) has a weight cut (S, T) and the rights of all sides. Minimum cut problem requires a network G, the minimum weight cut.
Platform: | Size: 336896 | Author: yjian | Hits:

[Data structsnfa

Description: 把NFA确定化为DFA 的算法,实现将给定的NFA M,确定化为DFA M’,然后将DFA M状态最少化,将给定的DFA M的有限状态集S划分成若干互不相交的子集,使得:任何不同的两个子集中的状态都是可区别的,而同一子集中的任何两个状态都是等价的(要利用Ia函数,但并不需要构造ε-CLOSURE函数,因这是DFA)。输出化简后的DFA M’。 -NFA into a DFA to determine the algorithm to achieve a given NFA M, to determine into a DFA M ' , then the DFA M state minimization, given DFA M of finite state set S is divided into several disjoint subset, such that: any two different subset of the state are distinguishable, and the same subset of any two states are equivalent (to take advantage of Ia function, but does not need to construct ε-CLOSURE function, because This is a DFA). Output of the simplified DFA M ' .
Platform: | Size: 2048 | Author: 王静晓 | Hits:

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