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Truthful mechanism design for multidimensional scheduling via cycle monotonicity

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  • Lavi, Ron
  • Swamy, Chaitanya

Abstract

We consider the makespan-minimization problem on unrelated machines in the context of algorithmic mechanism design. No truthful mechanisms with non-trivial approximation guarantees are known for this multidimensional domain. We study a well-motivated special case (also a multidimensional domain), where the processing time of a job on each machine is either "low" or "high." We give a general technique to convert any c-approximation algorithm (in a black-box fashion) to a 3c-approximation truthful-in-expectation mechanism. Our construction uses fractional truthful mechanisms as a building block, and builds upon a technique of Lavi and Swamy [Lavi, R., Swamy, C., 2005. Truthful and near-optimal mechanism design via linear programming. In: Proc. 46th FOCS, pp. 595-604]. When all jobs have identical low and high values, we devise a deterministic 2-approximation truthful mechanism. The chief novelty of our results is that we do not utilize explicit price definitions to prove truthfulness. Instead we design algorithms that satisfy cycle monotonicity [Rochet, J., 1987. A necessary and sufficient condition for rationalizability in a quasilinear context. J. Math. Econ. 16, 191-200], a necessary and sufficient condition for truthfulness in multidimensional settings; this is the first work that leverages this characterization.

Suggested Citation

  • Lavi, Ron & Swamy, Chaitanya, 2009. "Truthful mechanism design for multidimensional scheduling via cycle monotonicity," Games and Economic Behavior, Elsevier, vol. 67(1), pages 99-124, September.
  • Handle: RePEc:eee:gamebe:v:67:y:2009:i:1:p:99-124
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    References listed on IDEAS

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    1. Nisan, Noam & Ronen, Amir, 2001. "Algorithmic Mechanism Design," Games and Economic Behavior, Elsevier, vol. 35(1-2), pages 166-196, April.
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    Cited by:

    1. Leah Epstein & Asaf Levin & Rob van Stee, 2016. "A Unified Approach to Truthful Scheduling on Related Machines," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 332-351, February.
    2. Penna, Paolo & Ventre, Carmine, 2014. "Optimal collusion-resistant mechanisms with verification," Games and Economic Behavior, Elsevier, vol. 86(C), pages 491-509.
    3. Emerson Melo, 2018. "A Variational Approach to Network Games," Working Papers 2018.05, Fondazione Eni Enrico Mattei.
    4. Leucci, Stefano & Mamageishvili, Akaki & Penna, Paolo, 2018. "No truthful mechanism can be better than n approximate for two natural problems," Games and Economic Behavior, Elsevier, vol. 111(C), pages 64-74.
    5. Georgiou, Konstantinos & Swamy, Chaitanya, 2019. "Black-box reductions for cost-sharing mechanism design," Games and Economic Behavior, Elsevier, vol. 113(C), pages 17-37.
    6. Itai Ashlagi & Shahar Dobzinski & Ron Lavi, 2012. "Optimal Lower Bounds for Anonymous Scheduling Mechanisms," Mathematics of Operations Research, INFORMS, vol. 37(2), pages 244-258, May.
    7. Dominik Kress & Sebastian Meiswinkel & Erwin Pesch, 2018. "Mechanism design for machine scheduling problems: classification and literature overview," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 583-611, July.
    8. Debasis Mishra & Anup Pramanik & Souvik Roy, 2013. "Implementation in multidimensional domains with ordinal restrictions," Discussion Papers 13-07, Indian Statistical Institute, Delhi.
    9. Mu'alem, Ahuva & Schapira, Michael, 2018. "Setting lower bounds on truthfulness," Games and Economic Behavior, Elsevier, vol. 110(C), pages 174-193.

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