Optimization Issues in Combinatorial Auctions

Auctions are used more and more to sell a large variety of goods. In this chapter, it is our objective to concentrate on applications of auctions in telecommunication, which possess a part or a feature that can be optimized. Optimization methods are necessary, in particular, when auctions are used to sell or purchase goods which consist of combinations of items, and where combinations have higher or lower value than the sum of values of individual items: combinatorial auctions. In the first part, we review the theory on combinatorial auctions, starting with the various properties and mechanisms found in the literature on combinatorial auctions. Then the allocation decision is identified as the winner determination problem (WDP), which is the central subject of this chapter. The winner determination problem is formulated as an Integer Linear Program (ILP) with the structure of a set-packing problem. Therefore, complexity results, polynomial special cases, and general solution methods for the WDP are often obtained from results for the set-packing problem. In the second part of this chapter, we turn to applications from telecommunications. First, a model for bandwidth allocation in networks is discussed. The problem is translated into a formulation that has close relations to multi-commodity flow and network synthesis. This guides us to alternative formulations and to solution methods. Second, the auctions of radio spectrum in the US and Europe are reviewed. The WDP of these multi-round auctions can be modeled using the XOR-of-OR bidding language, and solved by methods originally developed for set-packing.

[1]  F. Gavril The intersection graphs of subtrees in tree are exactly the chordal graphs , 1974 .

[2]  Noam Nisan,et al.  Bidding and allocation in combinatorial auctions , 2000, EC '00.

[3]  Sven de Vries,et al.  A Branch-and-Price Algorithm and New Test Problems for Spectrum Auctions , 2005, Manag. Sci..

[4]  Kazuo Murota,et al.  Application of M-Convex Submodular Flow Problem to Mathematical Economics , 2001, ISAAC.

[5]  E. Maskin,et al.  The Implementation of Social Choice Rules: Some General Results on Incentive Compatibility , 1979 .

[6]  Robert C. Holte,et al.  Combinatorial Auctions, Knapsack Problems, and Hill-Climbing Search , 2001, Canadian Conference on AI.

[7]  Yoav Shoham,et al.  A Test Suite for Combinatorial Auctions , 2005 .

[8]  Ronald M. Harstad,et al.  Computationally Manageable Combinational Auctions , 1998 .

[9]  Sven de Vries,et al.  Combinatorial Auctions: A Survey , 2003, INFORMS J. Comput..

[10]  Moshe Tennenholtz Some Tractable Combinatorial Auctions , 2000, AAAI/IAAI.

[11]  Akiyoshi Shioura,et al.  Minimization of an M-convex Function , 1998, Discret. Appl. Math..

[12]  William Vickrey,et al.  Counterspeculation, Auctions, And Competitive Sealed Tenders , 1961 .

[13]  D. Lehmann,et al.  The Winner Determination Problem , 2003 .

[14]  Ennio Stacchetti,et al.  The English Auction with Differentiated Commodities , 2000, J. Econ. Theory.

[15]  Noam Nisan,et al.  Bidding Languages for Combinatorial Auctions , 2005 .

[16]  Rudolf Müller,et al.  Optimization in electronic markets: examples in combinatorial auctions , 2001 .

[17]  Subhash Suri,et al.  Vickrey prices and shortest paths: what is an edge worth? , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.

[18]  D. Gale,et al.  Multi-Item Auctions , 1986, Journal of Political Economy.

[19]  V. Crawford,et al.  Job Matching, Coalition Formation, and Gross Substitutes , 1982 .

[20]  Andrew T. Campbell,et al.  Pricing, provisioning and peering: dynamic markets for differentiated Internet services and implications for network interconnections , 2000, IEEE Journal on Selected Areas in Communications.

[21]  Kazuo Murota,et al.  Discrete convexity and equilibria in economies with indivisible goods and money , 2001, Math. Soc. Sci..

[22]  J. Potters,et al.  Verifying gross substitutability , 2002 .

[23]  S. Shenker,et al.  Pricing in computer networks: reshaping the research agenda , 1996, CCRV.

[24]  F. Spieksma On the approximability of an interval scheduling problem , 1999 .

[25]  Moshe Tennenholtz,et al.  Constrained multi-object auctions and b-matching , 2000, Inf. Process. Lett..

[26]  Kazuo Murota,et al.  New characterizations of M-convex functions and their applications to economic equilibrium models with indivisibilities , 2003, Discret. Appl. Math..

[27]  Sushil Bikhchandani,et al.  The Package Assignment Model , 2002, J. Econ. Theory.

[28]  R. Myerson Incentive Compatibility and the Bargaining Problem , 1979 .

[29]  Zaifu Yang,et al.  A Note on Kelso and Crawford's Gross Substitutes Condition , 2003, Math. Oper. Res..

[30]  Michel Gendreau,et al.  Design issues for combinatorial auctions , 2004, 4OR.

[31]  Patrick Maillé,et al.  Multibid auctions for bandwidth allocation in communication networks , 2004, IEEE INFOCOM 2004.

[32]  Faruk Gul,et al.  WALRASIAN EQUILIBRIUM WITH GROSS SUBSTITUTES , 1999 .

[33]  Zaifu Yang,et al.  The Max-Convolution Approach to Equilibrium Models with Indivisibilities (Applications of Discrete Convex Analysis to Game Theory and Mathematical Economics) , 2004 .

[34]  Tuomas Sandholm,et al.  Algorithm for optimal winner determination in combinatorial auctions , 2002, Artif. Intell..

[35]  Lawrence M. Ausubel,et al.  The Lovely but Lonely Vickrey Auction , 2004 .

[36]  Lawrence M. Ausubel An Efficient Ascending-Bid Auction for Multiple Objects , 2004 .

[37]  Rudolf Müller,et al.  Tractable cases of the winner determination problem , 2006 .