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Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation

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Algorithmic Decision Theory (ADT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6992))

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Abstract

This paper is devoted to a knapsack problem with a cardinality constraint when dropping the assumption of additive representability [10]. More precisely, we assume that we only have a classification of the items into ordered classes. We aim at generating the set of preferred subsets of items, according to a pairwise dominance relation between subsets that naturally extends the ordering relation over classes [4,16]. We first show that the problem reduces to a multiobjective knapsack problem with cardinality constraint. We then propose two polynomial algorithms to solve it, one based on a multiobjective dynamic programming scheme and the other on a multiobjective branch and bound procedure. We conclude by providing numerical tests to compare both approaches.

This research has been supported by the project ANR-09-BLAN-0361 GUaranteed Efficiency for PAReto optimal solutions Determination (GUEPARD).

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References

  1. Barberà, S., Bossert, W., Pattanaik, P.K.: Ranking sets of objects. In: Barberà, S., Hammond, P.J., Seidl, C. (eds.) Handbook of Utility Theory, vol. 2, Kluwer Academic Publishers, Dordrecht (2004)

    Chapter  Google Scholar 

  2. Bartee, E.M.: Problem solving with ordinal measurement. Management Science 17(10), 622–633 (1971)

    Article  Google Scholar 

  3. Bossert, W., Pattanaik, P.K., Xu, Y.: Ranking opportunity sets: An axiomatic approach. Journal of Economic Theory 63(2), 326–345 (1994)

    Article  MathSciNet  Google Scholar 

  4. Bossong, U., Schweigert, D.: Minimal paths on ordered graphs. Technical Report 24, Report in Wirtschaftsmathematik, Universität Kaiserslautern (1996)

    Google Scholar 

  5. Bouveret, S., Endriss, U., Lang, J.: Fair division under ordinal preferences: Computing envy-free allocations of indivisible goods. In: European Conference on Artificial Intelligence (ECAI 2010), pp. 387–392. IOS Press, Amsterdam (2010)

    Google Scholar 

  6. Brams, S., Edelman, P., Fishburn, P.: Fair division of indivisible items. Theory and Decision 5(2), 147–180 (2004)

    Article  MathSciNet  Google Scholar 

  7. Brams, S., King, D.: Efficient fair division – help the worst off or avoid envy? Rationality and Society 17(4), 387–421 (2005)

    Article  Google Scholar 

  8. Della Croce, F., Paschos, V.T., Tsoukias, A.: An improved general procedure for lexicographic bottleneck problems. Op. Res. Letters 24, 187–194 (1999)

    Article  MathSciNet  Google Scholar 

  9. Erlebach, T., Kellerer, H., Pferschy, U.: Approximating multi-objective knapsack problems. In: Dehne, F., Sack, J.-R., Tamassia, R. (eds.) WADS 2001. LNCS, vol. 2125, pp. 210–221. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  10. Fishburn, P.C.: Utility Theory for Decision Making. Wiley, New York (1970)

    Book  Google Scholar 

  11. Fishburn, P.C.: Signed orders and power set extensions. Journal of Economic Theory 56, 1–19 (1992)

    Article  MathSciNet  Google Scholar 

  12. Halpern, J.Y.: Defining relative likelihood in partially-ordered preferential structures. Journal of Artificial Intelligence Research 7, 1–24 (1997)

    Article  MathSciNet  Google Scholar 

  13. Hansen, P.: Bicriterion path problems. In: Fandel, G., Gal, T. (eds.) Multicriteria Decision Making (1980)

    Google Scholar 

  14. Klamler, C., Pferschy, U., Ruzika, S.: Committee selection with a weight constraint based on lexicographic rankings of individuals. In: Rossi, F., Tsoukias, A. (eds.) ADT 2009. LNCS, vol. 5783, pp. 50–61. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Klamroth, K., Wiecek, M.M.: Dynamic programming approaches to the multiple criteria knapsack problem. Naval Research Logistics 47, 57–76 (2000)

    Article  MathSciNet  Google Scholar 

  16. Schweigert, D.: Ordered graphs and minimal spanning trees. Foundations of Computing and Decision Sciences 24(4), 219–229 (1999)

    MathSciNet  MATH  Google Scholar 

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Delort, C., Spanjaard, O., Weng, P. (2011). Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation. In: Brafman, R.I., Roberts, F.S., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2011. Lecture Notes in Computer Science(), vol 6992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24873-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-24873-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24872-6

  • Online ISBN: 978-3-642-24873-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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