A heuristic for Dijkstra’s algorithm with many targets and its use in weighted matching algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2161, Issue , 2001, Pages 242-253

  Mehlhorn, Kurt ^a   Schäfer, Guido ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DIRECTED GRAPHS;

EDGE WEIGHTS; NON NEGATIVES; SHORTEST PATH; SHORTEST PATH PROBLEM; SINGLE SOURCE; WEIGHTED BIPARTITE MATCHINGS; WEIGHTED MATCHING; WEIGHTED MATCHING ALGORITHMS;

HEURISTIC ALGORITHMS;

EID: 33644581725     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44676-1_20     Document Type: Conference Paper

References (6)

1. R.K. Ahuja, T.L. Magnanti, and J.B. Orlin. Network Flows. Prentice Hall, 1993.
2. N. Alon, J.H. Spencer, and P. Erdös. The Probabilistic Method. John Wiley & Sons, 1992.
3. Z. Galil. Efficient algorithms for finding maximum matching in graphs. ACM Computing Surveys, 18(1):23-37, 1986.
4. K. Mehlhorn and S. Näher. The LEDA Platform for Combinatorial and Geometric Computing. Cambridge University Press, 1999. 1018 pages.
5. K. Mehlhorn and G. Schäfer. Implementation of O(nmlogn) weighted matchings in general graphs: The power of data structures. In Workshop on Algorithm Engineering (WAE), Lecture Notes in Computer Science, to appear, 2000. www.mpi-sb.mpg.de/~mehlhorn/ftp/WAE00.ps.gz.
6. G. Schäfer. Weighted matchings in general graphs. Master’s thesis, Fachbereich Informatik, Universität des Saarlandes, Saarbrücken, Germany, 2000.