Skip to main content

A unified approach to projective algorithms for linear programming

  • Conference paper
  • First Online:
Optimization

Part of the book series: Lecture Notes in Mathematics ((LNM,volume 1405))

Abstract

In this paper it is shown that a projective algorithm based on the minimization of a potential function by a constrained Newton method is general enough to include other known projective methods for linear programming and fractional linear programming. It also provides a framework to analyze affine interior point methods and to relate them to projective methods.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 34.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 46.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adler, I., Karmarkar, N, Resende, M.C.G. and Veiga, G., “An implementation of Karmarkar's algorithm for linear programming”, Working Paper Operations Research Center, University of California, (Berkeley, California, 1986).

    MATH  Google Scholar 

  2. Anstreicher, K. M., “A monotonic projective algorithm for fractional linear programming”, Algorithmica 1 (1986), 483–498.

    Article  MathSciNet  MATH  Google Scholar 

  3. Anstreicher, K.M., “A combined ‘phase I — phase II’ projective algorithm for linear programming”, manuscript, Yale School of Organization and Management (1986), to appear in Mathematical programming.

    Google Scholar 

  4. Barnes, E.R., “A variation on Karmarkar's algorithm for solving linear programming problems”, Mathematical Programming 36 (1986), 174–182.

    Article  MathSciNet  MATH  Google Scholar 

  5. de Ghellinck, G. and Vial, J.-P., “An extension of Karmarkar's algorithm for solving a system of linear homogeneous equations on the simplex”, Mathematical Programming 36 (1987), 79–92.

    Article  MATH  Google Scholar 

  6. de Ghellinck, G. and Vial, J.-P., “A polynomial Newton method for linear programming”, Algorithmica 1 (1986), 425–453.

    Article  MathSciNet  MATH  Google Scholar 

  7. Dikin, I.I., “Iterative solution of problems of linear and quadratic programming”, Doklady Akademiia Nauk SSSR 174 (1967), 747–748, [English translation: Soviet Mathematics Doklady 8, 674–675].

    MathSciNet  MATH  Google Scholar 

  8. Gay, D., “A variant of Karmarkar's linear programming algorithm for problems in standard form”, Mathematical Programming 37 (1987), 81–90.

    Article  MathSciNet  MATH  Google Scholar 

  9. Gill, P.E., Murray, W., Saunders, M.A., Tomlin, J.A. and Wright, M.H., “On projected Newton barrier methods for linear programming and an equivalence to Karmarkar's projective method”, Mathematical Programming 36 (1986), 183–209.

    Article  MathSciNet  MATH  Google Scholar 

  10. Goffin, J.-L., “Affine methods in non-differentiable optimization”, CORE discussion paper 8744, Center for Operations Research and Econometrics, (Louvain la Neuve, Belgium, 1987).

    Google Scholar 

  11. Goldfarb, D. and Mehrotra, S., “A relaxed version of Karmarkar's method”, Mathematical Programming 40 (1988), 289–315.

    Article  MathSciNet  MATH  Google Scholar 

  12. Goldfarb, D. and Mehrotra, S., “Relaxed variants of Karmarkar's algorithm for linear programs with unknown optimal objective value”, Mathematical Programming 40 (1988), 183–195.

    Article  MathSciNet  MATH  Google Scholar 

  13. Gonzaga, C., “A conical projection algorithm for linear programming”, (1985), to appear in Mathematical Programming.

    Google Scholar 

  14. Gonzaga, C., “An algorithm for solving linear programming in O(n3L) operations”, in Progress in Mathematical Programming, Megiddo N. ed., Springer Verlag 1988, 1–28.

    Google Scholar 

  15. Gonzaga, C., “Search directions for interior linear programming methods”, Memorandum N0 UCB/ERL M87/44, Electronics Research Laboratory, College of Engineering, University of California (Berkeley, California, 1987).

    MATH  Google Scholar 

  16. Iri, M. and Imai, H., “A multiplicative penalty function method for linear programming”, Algorithmica 1 (1986), 455–482.

    Article  MathSciNet  MATH  Google Scholar 

  17. Karmarkar, N., “A new polynomial time algorithm for linear programming”, Combinatorica 4 (4) (1984), 373–395.

    Article  MathSciNet  MATH  Google Scholar 

  18. Kojima, M., Mizuno, S. and Yoshishe, A., “A primal-dual interior point method for linear programming”, in Progress in Mathematical Programming, Megiddo N. editor, Springer Verlag 1988, 29–47.

    Google Scholar 

  19. Megiddo, N., “Introduction: new approaches to linear programming”, Algorithmica 1 (1986), 387–394.

    Article  MathSciNet  MATH  Google Scholar 

  20. Megiddo, N. and Shub, M., “Boundary behaviour of interior point algorithms in linear programming”, Research report RJ 5319, IBM Thomas J. Watson Research Center (Yorktown Heights, New York, 1986).

    MATH  Google Scholar 

  21. Mitchell, J. and Todd, M., “On the relationship between the search directions in the affine and projective variants of Karmarkar's linear programming algorithm”, Technical report no 725, School of Operations Research, Cornell University (Ithaca, New York, dec.86).

    Google Scholar 

  22. Monteiro, R.C. and Adler, I., “An O(n3L) primal-dual interior point algorithm for linear programming”, to appear in Masthematical Programming.

    Google Scholar 

  23. Renegar, J., “A Polynomial-Time algorithm based on Newton's method for linear programming”, Mathematical Programming 40, (1988), 59–93.

    Article  MathSciNet  MATH  Google Scholar 

  24. Todd, M.J., Burrell, B.P., An extension of Karmarkar's algorithm for linear programming using dual variables, Algorithmica 1, (1986) 409–424.

    Article  MathSciNet  MATH  Google Scholar 

  25. Vaidya, P.M., “An algorithm for linear programming which requires O(((m+n)n2+(m+n)1.5)L) arithmetic operations”, preprint, AT&T Bell Laboratories (Murray Hills, New Jersey, 1987).

    Google Scholar 

  26. Vanderbei, R.J., Meketon, M.S. and Freedman, B.A., “A modification of Karmarkar's linear programming algorithm”, Algorithmica. 1 (1986), 395–407.

    Article  MathSciNet  MATH  Google Scholar 

  27. Vial, J.-Ph., “Strong and weak convexity of sets and functions”, Mathematics of Operations Research 8 (2), (1983), 231–259.

    Article  MathSciNet  MATH  Google Scholar 

  28. Vial, J.-Ph., “Approximate projections in a projective method for the linear feasibility problem”, in Progress in Mathematical Programming, Megiddo N. ed., Springer Verlag, (1988), 65–78.

    Google Scholar 

  29. Vial, J.-Ph., “A fully polynomial time algorithm for linear programming”, Operations Research Letters, (1988), 15–19.

    Google Scholar 

  30. Yamashita, H., “A polynomially and quadratically convergent method for linear programming”, manuscript, Mathematical Systems Institute Inc., (Shinjuku-ku, Tokyo, 1986).

    Google Scholar 

  31. Ye Y. and Kojima M., “Recovering optimal dual solutions in Karmarkar's polynomial algorithm for linear programming”, Mathematical Programming 39 (1987), 305–317.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Szymon Dolecki

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer Verlag

About this paper

Cite this paper

Vial, JP. (1989). A unified approach to projective algorithms for linear programming. In: Dolecki, S. (eds) Optimization. Lecture Notes in Mathematics, vol 1405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0083596

Download citation

  • DOI: https://doi.org/10.1007/BFb0083596

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-51970-6

  • Online ISBN: 978-3-540-46867-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics