The Submodular Santa Claus Problem in the Restricted Assignment Case

Authors Etienne Bamas, Paritosh Garg, Lars Rohwedder



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Author Details

Etienne Bamas
  • EPFL, Lausanne, Switzerland
Paritosh Garg
  • EPFL, Lausanne, Switzerland
Lars Rohwedder
  • EPFL, Lausanne, Switzerland

Acknowledgements

The authors wish to thank Ola Svensson for helpful discussions on the problem.

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Etienne Bamas, Paritosh Garg, and Lars Rohwedder. The Submodular Santa Claus Problem in the Restricted Assignment Case. In 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 198, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ICALP.2021.22

Abstract

The submodular Santa Claus problem was introduced in a seminal work by Goemans, Harvey, Iwata, and Mirrokni (SODA'09) as an application of their structural result. In the mentioned problem n unsplittable resources have to be assigned to m players, each with a monotone submodular utility function f_i. The goal is to maximize min_i f_i(S_i) where S₁,...,S_m is a partition of the resources. The result by Goemans et al. implies a polynomial time O(n^{1/2 +ε})-approximation algorithm. Since then progress on this problem was limited to the linear case, that is, all f_i are linear functions. In particular, a line of research has shown that there is a polynomial time constant approximation algorithm for linear valuation functions in the restricted assignment case. This is the special case where each player is given a set of desired resources Γ_i and the individual valuation functions are defined as f_i(S) = f(S ∩ Γ_i) for a global linear function f. This can also be interpreted as maximizing min_i f(S_i) with additional assignment restrictions, i.e., resources can only be assigned to certain players. In this paper we make comparable progress for the submodular variant: If f is a monotone submodular function, we can in polynomial time compute an O(log log(n))-approximate solution.

Subject Classification

ACM Subject Classification
  • Theory of computation → Scheduling algorithms
Keywords
  • Scheduling
  • submodularity
  • approximation algorithm
  • hypergraph matching

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References

  1. Chidambaram Annamalai, Christos Kalaitzis, and Ola Svensson. Combinatorial algorithm for restricted max-min fair allocation. ACM Trans. Algorithms, 13(3):37:1-37:28, 2017. URL: https://doi.org/10.1145/3070694.
  2. Arash Asadpour, Uriel Feige, and Amin Saberi. Santa claus meets hypergraph matchings. ACM Trans. Algorithms, 8(3), 2012. URL: https://doi.org/10.1145/2229163.2229168.
  3. Nikhil Bansal and Maxim Sviridenko. The santa claus problem. In Proceedings of the Thirty-Eighth Annual ACM Symposium on Theory of Computing, STOC ’06, page 31–40, New York, NY, USA, 2006. Association for Computing Machinery. URL: https://doi.org/10.1145/1132516.1132522.
  4. Deeparnab Chakrabarty, Julia Chuzhoy, and Sanjeev Khanna. On allocating goods to maximize fairness. In 50th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2009, October 25-27, 2009, Atlanta, Georgia, USA, pages 107-116. IEEE Computer Society, 2009. URL: https://doi.org/10.1109/FOCS.2009.51.
  5. Siu-Wing Cheng and Yuchen Mao. Restricted max-min fair allocation. In Ioannis Chatzigiannakis, Christos Kaklamanis, Dániel Marx, and Donald Sannella, editors, 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018, July 9-13, 2018, Prague, Czech Republic, volume 107 of LIPIcs, pages 37:1-37:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. URL: https://doi.org/10.4230/LIPIcs.ICALP.2018.37.
  6. Siu-Wing Cheng and Yuchen Mao. Restricted max-min allocation: Approximation and integrality gap. In 46th International Colloquium on Automata, Languages, and Programming, ICALP 2019, July 9-12, 2019, Patras, Greece, pages 38:1-38:13, 2019. URL: https://doi.org/10.4230/LIPIcs.ICALP.2019.38.
  7. Sami Davies, Thomas Rothvoss, and Yihao Zhang. A tale of santa claus, hypergraphs and matroids. In Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, SODA 2020, Salt Lake City, UT, USA, January 5-8, 2020, pages 2748-2757, 2020. URL: https://doi.org/10.1137/1.9781611975994.167.
  8. Uriel Feige. On allocations that maximize fairness. In Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’08, page 287–293, USA, 2008. Society for Industrial and Applied Mathematics. Google Scholar
  9. Michel X Goemans, Nicholas JA Harvey, Satoru Iwata, and Vahab Mirrokni. Approximating submodular functions everywhere. In Proceedings of the twentieth annual ACM-SIAM symposium on Discrete algorithms, pages 535-544. SIAM, 2009. Google Scholar
  10. Klaus Jansen and Lars Rohwedder. A note on the integrality gap of the configuration lp for restricted santa claus. Information Processing Letters, 164:106025, 2020. URL: https://doi.org/10.1016/j.ipl.2020.106025.
  11. Andreas Krause, Ram Rajagopal, Anupam Gupta, and Carlos Guestrin. Simultaneous placement and scheduling of sensors. In Proceedings of the 8th International Conference on Information Processing in Sensor Networks, IPSN 2009, April 13-16, 2009, San Francisco, California, USA, pages 181-192. IEEE Computer Society, 2009. URL: http://ieeexplore.ieee.org/document/5211932/.
  12. Benny Lehmann, Daniel Lehmann, and Noam Nisan. Combinatorial auctions with decreasing marginal utilities. Games Econ. Behav., 55(2):270-296, 2006. URL: https://doi.org/10.1016/j.geb.2005.02.006.
  13. J. K. Lenstra, D. B. Shmoys, and E. Tardos. Approximation algorithms for scheduling unrelated parallel machines. In 28th Annual Symposium on Foundations of Computer Science (sfcs 1987), pages 217-224, 1987. URL: https://doi.org/10.1109/SFCS.1987.8.
  14. Robin A Moser and Gábor Tardos. A constructive proof of the general lovász local lemma. Journal of the ACM (JACM), 57(2):1-15, 2010. Google Scholar
  15. Lukas Polacek and Ola Svensson. Quasi-polynomial local search for restricted max-min fair allocation. In Artur Czumaj, Kurt Mehlhorn, Andrew Pitts, and Roger Wattenhofer, editors, Automata, Languages, and Programming, pages 726-737, Berlin, Heidelberg, 2012. Springer Berlin Heidelberg. Google Scholar
  16. Jan Vondrák. Optimal approximation for the submodular welfare problem in the value oracle model. In Cynthia Dwork, editor, Proceedings of the 40th Annual ACM Symposium on Theory of Computing, Victoria, British Columbia, Canada, May 17-20, 2008, pages 67-74. ACM, 2008. URL: https://doi.org/10.1145/1374376.1374389.
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