Skip to main content
Log in

On strongly polynomial dual simplex algorithms for the maximum flow problem

  • Published:
Mathematical Programming Submit manuscript

Abstract

Several pivot rules for the dual network simplex algorithm that enable it to solve a maximum flow problem on ann-node,m-arc network in at most 2nm pivots and O(n 2 m) time are presented. These rules are based on the concept of apreflow and depend upon the use of node labels which are either the lengths of a shortestpseudoaugmenting path from those nodes to the sink node orvalid underestimates of those lengths. Extended versions of our algorithms are shown to solve an important class of parametric maximum flow problems with no increase in the worst-case pivot and time bounds of these algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. R.K. Ahuja, T.L. Magnanti and J.B. Orlin,Network Flows: Theory, Algorithms, and Applications (Prentice Hall, Englewood Cliffs, NJ, 1993).

    Google Scholar 

  2. R.D. Armstrong, W. Chen, D. Goldfarb and Z. Jin, Strongly polynomial dual simplex methods for the maximum flow problem, Manuscript, Graduate School of Management, Rutgers University, Newark, NJ, 1994.

    Google Scholar 

  3. R.D. Armstrong and Z. Jin, A strongly polynomial dual (simplex) method for the max flow problem, Manuscript, Graduate School of Management, Rutgers University, Newark, NJ, 1992.

    Google Scholar 

  4. G. Gallo, M.D. Grigoriadis and R.E. Tarjan, A fast parametric maximum-flow algorithm and applications,SIAM J. Computing 18 (1989) 30–55.

    Article  MATH  MathSciNet  Google Scholar 

  5. A.V. Goldberg, A new max-flow algorithm, Technical Report MIT/LCS/TM 291, Laboratory for Computer Science, M.I.T., Cambridge, MA, 1985.

    Google Scholar 

  6. A.V. Goldberg and R.E. Tarjan, A new approach to the maximum flow problem,Journal of the Association of Computing Machinery 35 (1988) 921–940.

    MATH  MathSciNet  Google Scholar 

  7. A.V. Goldberg, M.D. Grigoriadis and R.E. Tarjan, Use of dynamic trees in a network simplex algorithm for the maximum flow problems,Mathematical Programming 50 (1991) 277–290.

    Article  MATH  MathSciNet  Google Scholar 

  8. D. Goldfarb and J. Hao, A primal simplex algorithm that solves the maximum flow problem in at mostnm pivots and O(n 2m) time,Mathematical Programming 47 (1990) 353–365.

    Article  MATH  MathSciNet  Google Scholar 

  9. D. Goldfarb and J. Hao, On strongly polynomial variants of the network simplex algorithm for the maximum flow problem,Operations Research Letters 10 (1991) 383–387.

    Article  MATH  MathSciNet  Google Scholar 

  10. M.D. Grigoriadis, An efficient implementation of the network simplex method,Mathematical Programming Study 26 (1986) 83–111.

    MATH  MathSciNet  Google Scholar 

  11. A.V. Karzanov, Determining the maximal flow in a network by the method of preflows,Soviet Math. Doklady 15 (1974) 434–437.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

This research was supported in part by NSF Grants DMS 91-06195, DMS 94-14438, and CDR 84-21402 and DOE Grant DE-FG02-92ER25126.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Goldfarb, D., Chen, W. On strongly polynomial dual simplex algorithms for the maximum flow problem. Mathematical Programming 78, 159–168 (1997). https://doi.org/10.1007/BF02614368

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02614368

Keywords

Navigation