Introduction to algorithms
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Scaling Algorithms for the Shortest Paths Problem
SIAM Journal on Computing
Shortest paths algorithms: theory and experimental evaluation
Mathematical Programming: Series A and B
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
Negative-Cycle Detection Algorithms
ESA '96 Proceedings of the Fourth Annual European Symposium on Algorithms
A greedy strategy for detecting negative cost cycles in networks
Future Generation Computer Systems - Special issue: High-speed networks and services for data-intensive grids: The DataTAG project
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In this paper, we present a comprehensive empirical analysis of the Vertex Contraction (VC) algorithm for the problem of checking whether a directed graph with positive and negative costs on its edges has a negative cost cycle (NCCD). VC is a greedy algorithm, first presented in [SK05], for NCCD and is the only known greedy strategy for this problem. In [SK05] we compared a naive implementation of VC with the “standard” Bellman-Ford (BF) algorithm for the same problem. We observed that our algorithm performed an order of magnitude better than the BF algorithm on a range of randomly generated inputs, thereby conclusively demonstrating the superiority of our approach. This paper continues the study of contrasting greedy and dynamic programming approaches, by comparing VC with a number of sophisticated implementations of the BF algorithm.