Competitive algorithms for the weighted list update problem

  • Fabrizio d'Amore
  • Alberto Marchetti-Spaccamela
  • Umberto Nanni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 519)


In this paper we present some deterministic and randomized algorithms for the Weight List Update Problem. In this framework a cost (weight) is associated to each item. The algorithms consist in modifying the well known Move-To-Front heuristic by adding randomness or counters in order to decide whether moving the accessed item. We prove that Random Move-To-Front and Counting Move-To-Front are 2-competitive against any static adversary, and that deterministic Move-To-Front does not share this property. We apply this approach to the management of non-modifiable trees by means of lists of successors proving that 2-competitivity property still holds.


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  1. [1]
    J. L. Bentley, and C. McGeogh, Amortized Analyses of Self-Organizing Sequential Search Heuristics, Communications of the ACM 28, 4 (April 1985), 404–411.Google Scholar
  2. [2]
    J. R. Bitner, Heuristics that Dynamically Organize Data Structures, SIAM J. of Computing 8, 1 (February 1979), 82–110.Google Scholar
  3. [3]
    S. Ben-David, A. Borodin, R. Karp, G. Tardos, and A. Wigderson, On the Power of Randomization in Online Algorithms, in Proceedings of the 20th ACM Annual Symposium on Theory of Computing, May 1990, 379–386.Google Scholar
  4. [4]
    F. d'Amore, U. Nanni, and A. Marchetti-Spaccamela, Robust Algorithms for Diagnosis, Technical Report, Dipartimento di Informatica e Sistemistica, Univ. of Roma “La Sapienza”, 1991.Google Scholar
  5. [5]
    S. Gnesi, U. Montanari, and A. Martelli, Dynamic programming as graph searching: An algebraic approach, Journal of ACM 28, (1981), 737–751.Google Scholar
  6. [6]
    J. H. Hester, and D. S. Hirschberg, Self-Organizing Linear Search, ACM Computing Surveys 17, 3 (September 1985), 295–311.Google Scholar
  7. [7]
    S. Irani, N. Reingold, J. Westbrook, and D. D. Sleator, Randomized Competitive Algorithms for the List Update Problem, in Proceedings of the 2nd ACM-SIAM Annual Symposium on Discrete Algorithms, San Francisco, CA, January 1991, 251–260.Google Scholar
  8. [8]
    S. Irani, Two Results on the List Update Problem, Technical Report TR-90-037, Computer Science Division, U.C. Berkeley, California, August 1990.Google Scholar
  9. [9]
    M. S. Manasse, L. A. McGeoch, and D. D. Sleator, Competitive Algorithms for Online Problems, in Proceedings of the 18th ACM Annual Symposium on Theory of Computing, May 1988, 322–333.Google Scholar
  10. [10]
    N. J. Nilsson, Principles of Artificial Intelligence, Springer Verlag, (1982).Google Scholar
  11. [11]
    R. Reiter, A Theory of Diagnosis from First Principles, Artificial Intelligence 32, (1987), 57–95.Google Scholar
  12. [12]
    R. Rivest, On Self-Organizing Sequential Search Heuristics, Communications of the ACM 19, 2 (February 1976), 63–67.Google Scholar
  13. [13]
    D. D. Sleator, and R. E. Tarjan, Amortized Efficiency of List Update and Paging Rules, Communications of the ACM 28, 2 (February 1985), 202–208.Google Scholar
  14. [14]
    R. E. Tarjan, Amortized Computational Complexity, SIAM J. Alg. Disc. Meth. 6, 2 (April 1985), 306–318.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Fabrizio d'Amore
    • 1
  • Alberto Marchetti-Spaccamela
    • 2
  • Umberto Nanni
    • 2
  1. 1.Dipartimento di Informatica e SistemisticaUniversità di Roma “La Sapienza”RomaItalia
  2. 2.Dipartimento di Matematica Pura ed ApplicataUniversità di L'AquilaL'AquilaItalia

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