Description: 在 VLSI 设计中,多点互连是物理设计阶段的关键问题之一,而互连的点数等于 2 或大于 2 分别对应于
Manhattan 空间上有障碍时的最短路径问题和最小 Steiner 树问题,显然前者是后者的基础.连接图是研究最短路径
问题的有效工具,已有的典型连接图包括基于轨迹的GC 和GT 以及基于自由区的GF 和GG.工作包括3个方面:设计并分析了在各种连接图上实现动态的点对之间的最短路径查询算法 分析了在各个连接图上构造 3-Steiner 树的算
法,对于已有的 GC 上的 3-Steiner 算法,将其 Steiner 顶点的候选集合规模从 O((e+p)
2
)降低到了 O((t+p)
2
),其中 e,t,p
分别表示边数、障碍极边数和顶点数 设计了在GG上的3-Steiner树构造算法,其平均情况时间复杂度只有Θ(t). -Abstract: Finding networks with minimal cost to connect points is a key problem in VLSI design, which can be
described as obstacle-avoiding shortest path and minimum Steiner tree problem according to whether the number of
points is greater than 2. Connection graphs, such as track based on graphs GC and GT and free area based graphs
GF and GG, are effective tools for the shortest path problem, which is the foundation of the Steiner tree problem.
The contribution of this paper includes three points: The dynamic algorithms for querying the shortest path between
two points on each connection graph are designed and analyzed for the first time secondly, all algorithms for
Steiner problem on each connection graph are analyzed The number of candidate Steiner points is reduced from
O((e+p)
2
) to O((t+p)
2
) in the 3-Steiner algorithm on GC, where e, t, p presents the number of edges, extreme edges
of obstacles and terminals An average Θ(t) algorithm for Platform: |
Size: 595968 |
Author:东方雨 |
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Description: Many interesting route planning problems can be solved by computing shortest paths
in a suitably modeled, weighted graph representing a transportation network. Such networks
are naturally road networks or timetable networks of public transportation. For
large networks, the classical Dijkstra algorithm to compute shortest paths is too slow.
And therefore have faster algorithms been developed in recent years. These new algorithms
have in common that they use precomputation and store auxiliary data to speedup
subsequent shortest-path queries. Platform: |
Size: 28672 |
Author:manolin |
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Description: Many interesting route planning problems can be solved by computing shortest paths
in a suitably modeled, weighted graph representing a transportation network. Such networks
are naturally road networks or timetable networks of public transportation. For
large networks, the classical Dijkstra algorithm to compute shortest paths is too slow.
And therefore have faster algorithms been developed in recent years. These new algorithms
have in common that they use precomputation and store auxiliary data to speedup
subsequent shortest-path queries. Platform: |
Size: 11264 |
Author:manolin |
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Description: 1998年, Watts和Strogatz 提出了小世界网络这一概念,并建立了WS模型。 实证结果表明,大多数的真实网络都具有小世界特性(较小的最短路径) 和聚类特性(较大的聚类系数) 。
WS小世界模型构造算法
1、从规则图开始：考虑一个含有N个点的最近邻耦合网络，它们围成一个环，其中每个节点都与它左右相邻的各K/2节点相连，K是偶数。
2、随机化重连：以概率p随机地从新连接网络中的每个边，即将边的一个端点保持不变，而另一个端点取为网络中随机选择的一个节点。其中规定，任意两个不同的节点之间至多只能有一条边，并且每一个节点都不能有边与自身相连。
-In 1998, Watts and Strogatz proposed the concept of the small world network, and the establishment of the WS model. The empirical results show that most real networks have small world (the smaller the shortest path) and clustering properties (high clustering coefficient).
WS small-world model construction algorithm
1, from the rules FIG: consider a nearest neighbor coupling network with N points, they are surrounded by a ring, wherein each node and its left and right adjacent to each of K/2 connected to the node, K is an even number.
The 2 randomized reconnection: randomly with probability p from the new connection on each side of the network, coming section of one of the endpoints remain unchanged, while the other endpoint is taken as the random selection of a node in the network. Which states that between any two different nodes can have at most one edge, and each node can not be connected to its own side. Platform: |
Size: 1140736 |
Author:李梅 |
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Description: A Fuzzy-Particle Swarm Optimization Based Algorithm for Solving Shortest Path
Problem.
Abstract—In this paper, an efficient particle swarm
optimization (PSO) algorithm based on fuzzy logic for solving
the single source shortest path problem (SPP) is proposed. A
particle encoding/decoding scheme has been devised for
particle-representation of the SPP parameters, which is free of
the previously randomized path construction methods in
computational problems like the SPP .The search capability of
PSO is diversified by hybridizing the PSO with fuzzy logic. The
local optimums will not be the point of convergence for the
particles and the global optimum will be found in a shorter
period of time if the PSO is correctly modified using fuzzy logic
rules. Numerical computation results on several networks with
random weights illustrate the efficiency of the proposed
method for computation of the shortest paths in networks Platform: |
Size: 203776 |
Author:mina |
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Description: Dijkstra s algorithm is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.[1][2]
The algorithm exists in many variants Dijkstra s original variant found the shortest path between two nodes,[2] but a more common variant fixes a single node as the source node and finds shortest paths the source to all other nodes in the -Dijkstra s algorithm is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.[1][2]
The algorithm exists in many variants Dijkstra s original variant found the shortest path between two nodes,[2] but a more common variant fixes a single node as the source node and finds shortest paths the source to all other nodes in the Platform: |
Size: 1024 |
Author:Dharmesh |
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Description: 蚁群算法作为新发展的一种模拟蚂蚁群体智能行为的仿生优化算法，它具有较强的鲁棒性、优良的分布式计算机制、易于与其他方法相结合等优点，本算法用来解决最短路径问题，并在TSP旅行商问题上取得较好的成效。同时也可以在他领域如图着色问题、车辆调度问题、集成电路设计、通讯网络、数据聚类进行参考。(Ant colony algorithm is a newly developed bionic optimization algorithm that simulates the ant colony intelligence behavior. It has the advantages of strong robustness, excellent distributed computer system, and easy combination with other methods. This algorithm is used to solve the shortest solution. Path problems, and achieved good results on TSP travel business issues. At the same time, it can also be referenced in such areas as image coloring, vehicle scheduling, integrated circuit design, communication networks, and data clustering.) Platform: |
Size: 1835008 |
Author:元气满满 |
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Description: 算法基础：打开算法之门pdf
本书介绍了什么是计算机算法，如何描述它们，以及如何来评估它们。这些计算机算法将提供：利用计算机搜索信息的简单方式；解决各种排序问题的方法；利用有向无环图和最短路径法来解决基本问题的方法(可用于建模公路网络，任务间的依赖及金融关系)；解决字符串(例如DNA结构)问题的方法；密码学背后的基本原理；数据压缩的基础知识；以及甚至一些没有人能够理解如何在计算机上用相当长的时间来解决的问题。(Algorithm basics: open the door to algorithms PDF
This book describes what computer algorithms are, how to describe them, and how to evaluate them. These computer algorithms will provide: a simple way to search for information using a computer; Methods to solve various sorting problems; The use of directed acyclic graphs and shortest path methods to solve basic problems (which can be used to model road networks, inter-task dependencies, and financial relationships); Methods for solving problems with strings, such as the structure of DNA; The basic principles behind cryptography; Basic knowledge of data compression; And even some problems that no one can understand how to solve in a computer for a considerable amount of time.) Platform: |
Size: 32765952 |
Author:星星LNG |
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Search - Shortest path algorithm in networks