Dijkstra's algorithm solves the single-source shortest path problem on any directed graph in O(m + n log n) time when a Fibonacci heap is used as the frontier set data structure. Here n is the number of vertices and m is the number of edges in the graph. If the graph is nearly acyclic, other algorit
Shortest path algorithms for nearly acyclic directed graphs
โ Scribed by Tadao Takaoka
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 496 KB
- Volume
- 203
- Category
- Article
- ISSN
- 0304-3975
No coin nor oath required. For personal study only.
โฆ Synopsis
Abuaiadh and Kingston gave an efficient algorithm for the single source shortest path problem for a nearly acyclic graph with O(m + n log t) computing time, where m and n are the numbers of edges and vertices of the given directed graph and t is the number of delete-min operations in the priority queue manipulation. They use the Fibonacci heap for the priority queue. If the graph is acyclic, we have t = 0 and the time complexity becomes O(m + n) which is linear and optimal. They claim that if the graph is nearly acyclic, t is expected to be small and the algorithm runs fast.
In the present paper, we take another definition of acyclicity. The degree of cyclicity, cyc(G), of graph G is defined by the maximum cardinality of the strongly connected components of G. When cyc(G) = k, we give an algorithm for the single source problem with O(m + n log k) time complexity. Finally we give a hybrid algorithm that incorporates the merits of the above two algorithms.
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