Beyond Moulin mechanisms

The only known general technique for designing truthful and approximately budget-balanced cost-sharing mechanisms with good efficiency or computational complexity properties is due to Moulin [1999. Incremental cost sharing: Characterization by coalition strategy-proofness. Soc. Choice Welfare 16 (2), 279-320]. For many fundamental cost-sharing applications, however, Moulin mechanisms provably suffer from poor budget-balance, poor economic efficiency, or both. We propose acyclic mechanisms, a new framework for designing truthful and approximately budget-balanced cost-sharing mechanisms. Acyclic mechanisms strictly generalize Moulin mechanisms and offer three important advantages. First, it is easier to design acyclic mechanisms than Moulin mechanisms: many classical primal-dual algorithms naturally induce a non-Moulin acyclic mechanism with good performance guarantees. Second, for important classes of cost-sharing problems, acyclic mechanisms have exponentially better budget-balance and economic efficiency than Moulin mechanisms. Finally, while Moulin mechanisms have found application primarily in binary demand games, we extend acyclic mechanisms to general demand games, a multi-parameter setting in which each bidder can be allocated one of several levels of service.

[1]  Bezalel Peleg,et al.  Axiomatizations of the core , 1992 .

[2]  Nikhil R. Devanur,et al.  Strategyproof cost-sharing mechanisms for set cover and facility location games , 2003, EC '03.

[3]  Stefano Leonardi,et al.  Cross-monotonic cost sharing methods for connected facility location games , 2004, Theor. Comput. Sci..

[4]  Jaroslaw Byrka An Optimal Bifactor Approximation Algorithm for the Metric Uncapacitated Facility Location Problem , 2007, APPROX-RANDOM.

[5]  Aravind Srinivasan,et al.  Cost-Sharing Mechanisms for Network Design , 2007, Algorithmica.

[6]  Vijay V. Vazirani,et al.  Primal-Dual RNC Approximation Algorithms for Set Cover and Covering Integer Programs , 1999, SIAM J. Comput..

[7]  Subhash Khot,et al.  Vertex cover might be hard to approximate to within 2-/spl epsiv/ , 2003, 18th IEEE Annual Conference on Computational Complexity, 2003. Proceedings..

[8]  Nicole Immorlica,et al.  Limitations of cross-monotonic cost sharing schemes , 2005, SODA '05.

[9]  Éva Tardos,et al.  Approximation algorithms for facility location problems (extended abstract) , 1997, STOC '97.

[10]  Samir Khuller,et al.  Greedy strikes back: improved facility location algorithms , 1998, SODA '98.

[11]  Vijay V. Vazirani,et al.  Approximation algorithms for metric facility location and k-Median problems using the primal-dual schema and Lagrangian relaxation , 2001, JACM.

[12]  Vasek Chvátal,et al.  A Greedy Heuristic for the Set-Covering Problem , 1979, Math. Oper. Res..

[13]  H. Moulin,et al.  Strategyproof sharing of submodular costs:budget balance versus efficiency , 2001 .

[14]  Subhash Khot On the power of unique 2-prover 1-round games , 2002, STOC '02.

[15]  Vijay V. Vazirani,et al.  An Approximation Algorithm for the Fault Tolerant Metric Facility Location Problem , 2003, Algorithmica.

[16]  Joan Feigenbaum,et al.  Hardness Results for Multicast Cost Sharing , 2002, FSTTCS.

[17]  Tim Roughgarden,et al.  New trade-offs in cost-sharing mechanisms , 2006, STOC '06.

[18]  Jochen Könemann,et al.  A group-strategyproof mechanism for Steiner forests , 2005, SODA '05.

[19]  Vijay V. Vazirani,et al.  Equitable Cost Allocations via Primal--Dual-Type Algorithms , 2008, SIAM J. Comput..

[20]  R. Ravi,et al.  An efficient cost-sharing mechanism for the prize-collecting Steiner forest problem , 2007, SODA '07.

[21]  Mohammad Mahdian,et al.  Approximation Algorithms for Metric Facility Location Problems , 2006, SIAM J. Comput..

[22]  Evangelos Markakis,et al.  Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP , 2002, JACM.

[23]  Guido Schäfer,et al.  Cost Sharing Methods for Makespan and Completion Time Scheduling , 2007, STACS.

[24]  Florian Schoppmann,et al.  Group-Strategyproof Cost Sharing for Metric Fault Tolerant Facility Location , 2008, SAGT.

[25]  Vijay V. Vazirani,et al.  Applications of approximation algorithms to cooperative games , 2001, STOC '01.

[26]  Mohammad Mahdian,et al.  Facility location and the analysis of algorithms through factor-revealing programs , 2004 .

[27]  Florian Schoppmann,et al.  To Be or Not to Be (Served) , 2007, WINE.

[28]  Éva Tardos,et al.  Group strategy proof mechanisms via primal-dual algorithms , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[29]  R. Ravi,et al.  When Trees Collide: An Approximation Algorithm for the Generalized Steiner Problem on Networks , 1995, SIAM J. Comput..

[30]  David C. Parkes,et al.  Iterative Combinatorial Auctions: Theory and Practice , 2000, AAAI/IAAI.

[31]  David P. Williamson,et al.  A general approximation technique for constrained forest problems , 1992, SODA '92.

[32]  Vijay V. Vazirani,et al.  Approximation Algorithms , 2001, Springer Berlin Heidelberg.

[33]  Martin Skutella,et al.  Cooperative facility location games , 2000, SODA '00.

[34]  Tim Roughgarden,et al.  Optimal Efficiency Guarantees for Network Design Mechanisms , 2007, IPCO.

[35]  Dorit S. Hochbaum,et al.  Heuristics for the fixed cost median problem , 1982, Math. Program..

[36]  Guido Schäfer,et al.  Singleton Acyclic Mechanisms and Their Applications to Scheduling Problems , 2008, SAGT.

[37]  H. Moulin Incremental cost sharing: Characterization by coalition strategy-proofness , 1999 .

[38]  Fabián A. Chudak,et al.  Improved Approximation Algorithms for the Uncapacitated Facility Location Problem , 2003, SIAM J. Comput..