[1]赵礼峰,黄奕雯. 基于矩阵运算K短路径算法[J].计算机技术与发展,2017,27(04):98-103.
　ZHAO Li-feng,HUANG Yi-wen. Research on K-shortest Path Algorithm with Matrix Operations[J].,2017,27(04):98-103.
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 基于矩阵运算K短路径算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年04期
页码:
98-103
栏目:
智能、算法、系统工程
出版日期:
2017-04-10

文章信息/Info

Title:
 Research on K-shortest Path Algorithm with Matrix Operations
文章编号:
1673-629X（2017)04-0098-06
作者:
 赵礼峰; 黄奕雯
 南京邮电大学 理学院
Author(s):
 ZHAO Li-feng; HUANG Yi-wen
关键词:
 ; 次短路径; 渐次短路径; 距离矩阵; 路径矩阵
Keywords:
 ; second shortest path; third shortest path; distance matrix; channel matrix
分类号:
TP301.6
文献标志码:
A
摘要:
 最短路问题是复杂网络中的经典问题,其求解算法层出不穷,各有优缺点.经典的算法包括Dijkstra算法、Ford算法和Floyd算法等,只能求解两节点间的一条最短路径.在实际生活中,还需要在大型网络中限定一些前提条件求解两点间次短、渐次短的路径问题.为此,提出了一种对距离矩阵和路径矩阵的迭代、替换算法,即从一个节点出发寻找其后继节点,同时通过比较路径长短得到两点间最短路径、次短路径和渐次短路径,并不断重复、替换.为验证所提算法的有效性,以一个大型网络的应用作为实例,应用Matlab对所提算法进行了仿真实验验证.仿真结果表明,所提算法能够在复杂大规模随机网络中满足求解指定顶点间最短、次短和渐次短路径的需要,具有较好的有效性和适用性.
Abstract:
 Shortest path problem is a classic problem in complex networks,and their solutions after another and all have their advantages and disadvantages.The algorithm of Dijkstra,Ford and Floyd are most classical among these algorithms.However,these algorithms are only for solving a shortest path between nodes.In real life,some limited prerequisites are needed to find the second shortest path and the third shortest path between two nodes in large-scale networks.Therefore,the iterating and displacement algorithm for distance matrix and path matrix is proposed,started from one node to its successor node then compared to find the first shortest path,the second shortest path and the third shortest path repeating and replacing constantly.In order to verify the effectiveness of the proposed algorithm,taking a large network as an example,Matlab is applied to identify it in simulation.It is demonstrated that the proposed algorithm can calculate the first shortest path,the second shortest path and the third shortest path in a complex large-scale random networks,with good validity and applicability.

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更新日期/Last Update: 2017-06-19