On the computational complexity of dynamic graph problems
Theoretical Computer Science
Shortest paths algorithms: theory and experimental evaluation
Mathematical Programming: Series A and B
An incremental algorithm for a generalization of the shortest-path problem
Journal of Algorithms
Experimental analysis of dynamic algorithms for the single source shortest paths problem
Journal of Experimental Algorithmics (JEA)
Fully dynamic algorithms for maintaining shortest paths trees
Journal of Algorithms
New dynamic algorithms for shortest path tree computation
IEEE/ACM Transactions on Networking (TON)
A Space Saving Trick for Directed Dynamic Transitive Closure and Shortest Path Algorithms
COCOON '01 Proceedings of the 7th Annual International Conference on Computing and Combinatorics
Fully dynamic shortest paths in digraphs with arbitrary arc weights
Journal of Algorithms
Performance Comparison of Algorithms for the Dynamic Shortest Path Problem
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Algorithms for Sensor and Ad Hoc Networks: Advanced Lectures (Lecture Notes in Computer Science)
Algorithms for Sensor and Ad Hoc Networks: Advanced Lectures (Lecture Notes in Computer Science)
Speeding Up Dynamic Shortest-Path Algorithms
INFORMS Journal on Computing
Landmark-based routing in dynamic graphs
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
| Hi-index | 0.00 |
A dynamic shortest-path algorithm is called a batch algorithm if it is able to handle graph changes that consist of multiple edge updates at a time. In this paper we focus on fully-dynamic batch algorithms for single-source shortest paths in directed graphs with positive edge weights. We give an extensive experimental study of the existing algorithms for the single-edge and the batch case, including a broad set of test instances. We further present tuned variants of the already existing SWSF-FP -algorithm being up to 15 times faster than SWSF-FP . A surprising outcome of the paper is the astonishing level of data dependency of the algorithms. More detailed descriptions and further experimental results of this work can be found in [1].