[1]赵礼峰,梁娟. 最短路问题的Floyd改进算法[J].计算机技术与发展,2014,24(08):31-34.
 ZHAO Li-feng,LIANG Juan. Improved Floyd Algorithm for Shortest Paths Problem[J].,2014,24(08):31-34.
点击复制

 最短路问题的Floyd改进算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年08期
页码:
31-34
栏目:
智能、算法、系统工程
出版日期:
2014-08-10

文章信息/Info

Title:
 Improved Floyd Algorithm for Shortest Paths Problem
文章编号:
1673-629X(2014)08-0031-04
作者:
 赵礼峰梁娟
 南京邮电大学 理学院
Author(s):
 ZHAO Li-fengLIANG Juan
关键词:
 最短路不含负回路网络Floyd改进算法迭代矩阵
Keywords:
 the shortest pathnetwork without negative loopimproved Floyd algorithmiterative matrix
分类号:
TP301.6
文献标志码:
A
摘要:
 目前在不含负回路的网络中,对于求解任意两节点之间最短路问题的方法有很多,Floyd算法是最经典的算法之一,但随着节点数量的增加,重复的计算量也随之增大,从而降低了计算效率。为此,文中通过迭代矩阵和下标标注法对Floyd算法进行了改进,改进后的算法既能快速地计算出网络中任意两节点之间的最短路长值,又能更直观地找出最短路径。通过具体实例分析表明,Floyd改进算法减少了重复计算,简化了路径标注方法,提高了计算效率。
Abstract:
 At present,there are many algorithms for solving the shortest path between any two points in the network without negative loop. Floyd algorithm is one of the most classical algorithms. But when the number of nodes increases,the amount of repeated calculation also increases which reduces the efficiency of the algorithm. Floyd algorithm is improved in this paper by using iterative matrix and sub-script tagging method. The improved algorithm not only can calculate the shortest path weights more quickly but also find shortest paths more directly. The specific instance analysis indicates that the improved algorithm reduces the repeated calculation and simplifies the path tagging method,which lead to the improvement of the computational efficiency.

相似文献/References:

[1]赵礼峰 宋常城 白睿.基于最小费用最大流问题的“排序”算法[J].计算机技术与发展,2011,(12):82.
 ZHAO Li-feng,SONG Chang-cheng,BAI Rui.Sequence Algorithm Based on Minimum Cost and Maximum Flow[J].,2011,(08):82.
[2]赵礼峰,蒋腾飞.无回路网络最短路径的一种新算法[J].计算机技术与发展,2013,(02):105.
 ZHAO Li-feng,JIANG Teng-fei.A New Algorithm for Shortest Path in DAG[J].,2013,(08):105.
[3]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
 ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(08):1.
[4]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
 LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(08):5.
[5]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
 HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(08):13.
[6]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
 HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(08):21.
[7]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
 LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(08):25.
[8]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
 WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(08):29.
[9]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
 LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(08):34.
[10]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
 SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(08):38.
[11]赵礼峰,梁娟. Ford算法的改进算法[J].计算机技术与发展,2015,25(07):72.
 ZHAO Li-feng,LIANG Juan. Improved Algorithm of Ford Algorithm[J].,2015,25(08):72.

更新日期/Last Update: 2015-03-17