*   Domaine de compétence Optimisation Combinatoire   *
  *    Séminaire
  o    2016 - 2017
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  o    2014 - 2015
  o    2013 - 2014
  o    2012 - 2013
  o    2011 - 2012
  o    2010 - 2011
  o    2009 - 2010
  o    2008 - 2009
  o    2007 - 2008
  o    2006 - 2007
  o    2005 - 2006
  o    2004 - 2005
  o    2003 - 2004
  *    Evénements
  *    Liens

Séminaires 2016 - 2017

Ceci est la page web du séminaire de l'équipe Optimisation Combinatoire du laboratoire G-SCOP, à Grenoble.

Sauf mention contraire, le séminaire de Mathématiques Discrètes a lieu le jeudi à 14h30 en Salle C319. Les responsables sont Louis Esperet et András Sebő, n'hésitez pas à les contacter.

15 septembre 2016 Sylvia Boyd
(Université d'Ottawa, Canada)
tba
8 septembre 2016 Alantha Newman
(G-SCOP)
The Alternating Stock Size Problem and the Gasoline Puzzle
  • Jeudi 15 septembre 2016 (à 14h30): Sylvia Boyd (Université d'Ottawa, Canada) : tba

    tba


  • Jeudi 8 septembre 2016 (à 14h30): Alantha Newman (G-SCOP) : The Alternating Stock Size Problem and the Gasoline Puzzle

    Given a set S of integers whose sum is zero, consider the problem of finding a permutation of these integers such that: (i) all prefixes of the ordering are non-negative, and (ii) the maximum value of a prefix sum is minimized. Kellerer et al. referred to this problem as the stock size problem and showed that it can be approximated to within 3/2. They also showed that an approximation ratio of 2 can be achieved via several simple algorithms.
    We consider a related problem, which we call the alternating stock size problem, where the number of positive and negative integers in the input set S are equal. The problem is the same as above, but we are additionally required to alternate the positive and negative numbers in the output ordering. This problem also has several simple 2-approximations. We show that it can be approximated to within 1.79.
    Then we show that this problem is closely related to an optimization version of the gasoline puzzle due to Lovasz, in which we want to minimize the size of the gas tank necessary to go around the track. We present a 2-approximation for this problem, using a natural linear programming relaxation whose feasible solutions are doubly stochastic matrices. Our novel rounding algorithm is based on a transformation that yields another doubly stochastic matrix with special properties, from which we can extract a suitable permutation.

    Joint work with Heiko Roeglin (Universitaet Bonn) and Johanna Seif (ENS Lyon).