Les effets de l’exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs

Adama Coulibaly; Jean-Pierre Crouzeix

RAIRO - Operations Research - Recherche Opérationnelle (2003)

  • Volume: 37, Issue: 2, page 99-117
  • ISSN: 0399-0559

Abstract

top
Potential functions in interior point methods are used to determine descent directions and to prove the convergence. They depend on a parameter which is usually taken equal to or greater than the size of the problem. Actually, smaller values give a better conditioning of the method near an optimal solution. This assertion is illustrated by a few numerical experiments.

How to cite

top

Coulibaly, Adama, and Crouzeix, Jean-Pierre. "Les effets de l’exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs." RAIRO - Operations Research - Recherche Opérationnelle 37.2 (2003): 99-117. <http://eudml.org/doc/244911>.

@article{Coulibaly2003,
abstract = {Les méthodes de points intérieurs en programmation linéaire connaissent un grand succès depuis l’introduction de l’algorithme de Karmarkar. La convergence de l’algorithme repose sur une fonction potentielle qui, sous sa forme multiplicative, fait apparaître un exposant $p$. Cet exposant est, de façon générale, choisi supérieur au nombre de variables $n$ du problème. Nous montrons dans cet article que l’on peut utiliser des valeurs de $p$ plus petites que $n$. Ceci permet d’améliorer le conditionnement de la méthode au voisinage de la solution optimale.},
author = {Coulibaly, Adama, Crouzeix, Jean-Pierre},
journal = {RAIRO - Operations Research - Recherche Opérationnelle},
keywords = {interior point methods; karmarkar algorithm; multiplicative and additive potential functions; barrier function; convexity},
language = {fre},
number = {2},
pages = {99-117},
publisher = {EDP-Sciences},
title = {Les effets de l’exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs},
url = {http://eudml.org/doc/244911},
volume = {37},
year = {2003},
}

TY - JOUR
AU - Coulibaly, Adama
AU - Crouzeix, Jean-Pierre
TI - Les effets de l’exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs
JO - RAIRO - Operations Research - Recherche Opérationnelle
PY - 2003
PB - EDP-Sciences
VL - 37
IS - 2
SP - 99
EP - 117
AB - Les méthodes de points intérieurs en programmation linéaire connaissent un grand succès depuis l’introduction de l’algorithme de Karmarkar. La convergence de l’algorithme repose sur une fonction potentielle qui, sous sa forme multiplicative, fait apparaître un exposant $p$. Cet exposant est, de façon générale, choisi supérieur au nombre de variables $n$ du problème. Nous montrons dans cet article que l’on peut utiliser des valeurs de $p$ plus petites que $n$. Ceci permet d’améliorer le conditionnement de la méthode au voisinage de la solution optimale.
LA - fre
KW - interior point methods; karmarkar algorithm; multiplicative and additive potential functions; barrier function; convexity
UR - http://eudml.org/doc/244911
ER -

References

top
  1. [1] Y. Chabrillac et J.-P. Crouzeix, Definiteness and semi-definiteness of quadratic forms. Linear Algebra Appl. 63 (1984) 283-292. Zbl0548.15027MR766515
  2. [2] A. Coulibaly, Méthodes de points intérieurs en programmation linéaire, Thèse de doctorat de l’Université Blaise Pascal. Clermont-Ferrand (1994). 
  3. [3] J.-P. Crouzeix, J.A. Ferland et S. Schaible, Generalized convexity of functions on affine subspaces and applications. Math. Programming 56 (1992) 223-232. Zbl0777.90056MR1183648
  4. [4] J.-P. Crouzeix et R. Kebbour, Index multiplicatifs de convexité/concavité et applications. Cahiers Centre Études Rech. Opér. 34 (1992) 7-24. Zbl0784.90071MR1199191
  5. [5] G. De Ghelinck et J.-Ph. Vial, A polynomial Newton method for linear programming. Algorithmica 1 (1989) 425-453. Zbl0629.90058MR880732
  6. [6] C.C. Gonzaga, A Simple presentation of Karmarkar’s algorithm, Technical Report. Department of Mathematics, Federal University of Santa Catarina, Brasil (2002). 
  7. [7] C.C. Gonzaga, Search direction for interior linear programming methods. Algorithmica 6 (1991) 153-181. Zbl0718.90064MR1093008
  8. [8] C.C. Gonzaga, On lower bounds updates in primal potential reduction methods for linear programming. Math. Programming 52 (1991). Zbl0754.90034MR1148179
  9. [9] E.V. Haynsworth, Determination of the inertia of a partitioned hermitian matrix. Linear Algebra Appl. 1 (1968) 73-81. Zbl0155.06304MR223392
  10. [10] H. Imaï, On the convexity of the multiplicative version of Karmarkar’s potential function. Math. Programming 40 (1988) 29-32. Zbl0657.90060
  11. [11] M. Iri et H. Imaï, A mutiplicative barrier function method for linear programming. Algorithmica 1 (1986) 455-482. Zbl0641.90048MR880733
  12. [12] N.K. Karmarkar, A new polynomial time algorithm for linear programming. Combinatorica 4 (1984) 373-395. Zbl0557.90065MR779900
  13. [13] N.K. Karmarkar et K.G. Ramakrishnan, Computational results of an interior point algorithm for large scale linear program. Math. Programming 52 (1991) 55-586. Zbl0739.90042MR1148186
  14. [14] M. Kojima, S. Mizumo et A. Yoshise, An O ( n L ) iteration potential reduction algorithm for linear complementarity problems, Research Report No. B-217. Department of Information Sciences, Tokyo Institute of Technology, Tokyo, Japan (1988). 
  15. [15] P. Maréchal, On the convexity of the multiplicative potential and penalty function and related topics. Math. Programming Ser. A 89 (2001) 505-516. Zbl0990.90130MR1814553
  16. [16] M.J. Todd et Y. Yu, A Centered projective algorithm for linear programming. Math. Oper. Res. 15 (1990) 508-529. Zbl0722.90044MR1064215
  17. [17] T. Tsuchiya, Quadratic convergence of the Iri–Imaïalgorithm for degenerate linear programming problems. J. Optim. Theory Appl. 87 (1995) 703-726. Zbl0840.90101
  18. [18] Y. Ye, K.O. Kortanek et S. Huang, Near boundary behavior of primal-dual potential reduction algorithm for linear programming. Math. Programming 58 (1993) 243-255. Zbl0780.90066MR1216493
  19. [19] S. Zhang, Convergence property of the Iri–Imaï algorithm for some smooth convex programming problems. J. Optim. Theory Appl. 82 (1994) 121-137. Zbl0819.90073

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.