ACM Home Page
Please provide us with feedback. Feedback
A faster strongly polynomial minimum cost flow algorithm
Full text PdfPdf (1.10 MB)
Source Annual ACM Symposium on Theory of Computing archive
Proceedings of the twentieth annual ACM symposium on Theory of computing table of contents
Chicago, Illinois, United States
Pages: 377 - 387  
Year of Publication: 1988
ISBN:0-89791-264-0
Author
James Orlin  Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 22,   Downloads (12 Months): 115,   Citation Count: 35
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/62212.62249
What is a DOI?

ABSTRACT

We present a new strongly polynomial algorithm for the minimum cost flow problem, based on a refinement of the Edmonds-Karp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of &Ogr;(n log n) shortest path problems on networks with n nodes and m arcs and runs in &Ogr;(n log n(m + n log n)) steps. Using a standard transformation, this approach yields an &Ogr;(m log n (m + n log n)) algorithm for the capacitated minimum cost flow problem. This algorithm improves the best previous strongly polynomial algorithm due to Galil and Tardos, by a factor of m/n. Our algorithm is even more efficient if the number of arcs with finite upper bounds, say m', is much less than m. In this case, the number of shortest path problems solved is &Ogr;((m + n) log n).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
AHUJA, R.K., GOLDBERG, A.V., ORLIN, J.B., AND TARJAN, R.E. Solving minimum cost flow problem by double scaling. To appear.
 
2
BLAND, R.G., AND jENSEN, D.L. On the computational behavior of a polynomial-time network flow algorithm. Technical Report 661, School of Operations Research and industrial Engineering, Cornell University, Ithaca, 1985.
 
3
COOK, S.A., AND RECKHOW, R.A. Time bounded random access machines. }. of Comput. System Sci. 7 (1973), 354-375.
 
4
DIJKSTRA, E. A note of two problems in connexion with graphs. Numeriche Mathematics 1 (1959), 269-271.
5
 
6
FREDMAN, M.L., AND TARJAN, R.E., Fibonacci heaps and their uses in network optimization algorithms. 25th IEEE Syrup. on Found. of Comp, Sci. (1984), 338-346.
 
7
 
8
GALIL, Z., AND TARDOS, E. An O(n2 (m + n log n) log n) rain-cost flow algorithm. Proc. 27th Annual Symp. of Found. of Comp. Sci. (1986), 136-146.
9
10
 
11
LAWLER, E.L. Combinatorial Optimization: Networks and Matroids. Holt, Rinehart and Winston, New York, 1976.
 
12
MEGIDDO, N. Towards a strongly polynomial algorithm for linear programming. SIAM j. of Computing 12(1983) 347-353.
 
13
ORLIN, J.B. Genuinely polynomial simplex and non-simplex algorithms for the minimum cost flow problem. Technical Report No. 1615-84, Sloan School of Management, M.I.T., Cambridge, 1984.
 
14
ROCK, H. Scating techniques for minimal cost network flows. In. V. Page, editor, Discrete Structures and Algorithms , Carl Hansen, Munich, 1980. pp 101-191.
 
15
 
16

CITED BY  36