IDEAS home Printed from https://ideas.repec.org/a/inm/ormoor/v46y2021i4p1599-1610.html
   My bibliography  Save this article

Tight Approximation for Unconstrained XOS Maximization

Author

Listed:
  • Yuval Filmus

    (The Henry and Marilyn Taub Faculty of Computer Science, Technion–Israel Institute of Technology, Haifa 3200003, Israel)

  • Yasushi Kawase

    (Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8656, Japan)

  • Yusuke Kobayashi

    (Research Institute for Mathematical Sciences, Kyoto University, Kyoto 606-8502, Japan)

  • Yutaro Yamaguchi

    (Graduate School and Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan)

Abstract

A set function is called XOS if it can be represented by the maximum of additive functions. When such a representation is fixed, the number of additive functions required to define the XOS function is called the width. In this paper, we study the problem of maximizing XOS functions in the value oracle model. The problem is trivial for the XOS functions of width 1 because they are just additive, but it is already nontrivial even when the width is restricted to 2. We show two types of tight bounds on the polynomial-time approximability for this problem. First, in general, the approximation bound is between O ( n ) and Ω ( n / l o g n ) , and exactly θ ( n / l o g n ) if randomization is allowed, where n is the ground set size. Second, when the width of the input XOS functions is bounded by a constant k ≥ 2, the approximation bound is between k − 1 and k − 1 − ɛ for any ɛ > 0. In particular, we give a linear-time algorithm to find an exact maximizer of a given XOS function of width 2, whereas we show that any exact algorithm requires an exponential number of value oracle calls even when the width is restricted to 3.

Suggested Citation

  • Yuval Filmus & Yasushi Kawase & Yusuke Kobayashi & Yutaro Yamaguchi, 2021. "Tight Approximation for Unconstrained XOS Maximization," Mathematics of Operations Research, INFORMS, vol. 46(4), pages 1599-1610, November.
  • Handle: RePEc:inm:ormoor:v:46:y:2021:i:4:p:1599-1610
    DOI: 10.1287/moor.2020.1088
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/moor.2020.1088
    Download Restriction: no

    File URL: https://libkey.io/10.1287/moor.2020.1088?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormoor:v:46:y:2021:i:4:p:1599-1610. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.