Optimal Efficiency Guarantees for Network Design Mechanisms

  • Authors:
  • Tim Roughgarden;Mukund Sundararajan

  • Affiliations:
  • Department of Computer Science, Stanford University, 353 Serra Mall, Stanford, CA 94305,;Department of Computer Science, Stanford University, 353 Serra Mall, Stanford, CA 94305,

  • Venue:
  • IPCO '07 Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization
  • Year:
  • 2007

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Abstract

A cost-sharing problem is defined by a set of players vying to receive some good or service, and a cost function describing the cost incurred by the auctioneer as a function of the set of winners. A cost-sharing mechanism is a protocol that decides which players win the auction and at what prices. Three desirable but provably mutually incompatible properties of a cost-sharing mechanism are: incentive-compatibility, meaning that players are motivated to bid their true private value for receiving the good; budget-balance, meaning that the mechanism recovers its incurred cost with the prices charged; and efficiency, meaning that the cost incurred and the value to the players served are traded off in an optimal way.Our work is motivated by the following fundamental question: for which cost-sharing problems are incentive-compatible mechanisms with good approximate budget-balance and efficiency possible? We focus on cost functions defined implicitly by NP-hard combinatorial optimization problems, including the metric uncapacitated facility location problem, the Steiner tree problem, and rent-or-buy network design problems. For facility location and rent-or-buy network design, we establish for the first time that approximate budget-balance and efficiency are simultaneously possible. For the Steiner tree problem, where such a guarantee was previously known, we prove a new, optimal lower bound on the approximate efficiency achievable by the wide and natural class of "Moulin mechanisms". This lower bound exposes a latent approximation hierarchy among different cost-sharing problems.