An Approximation Approach for Large-Scale Multi-unit Combinatorial Auctions with Reserve-Price Biddings

In this paper, an approach on an auction-based pricing mechanism is proposed that can be modeled as a variant of reserve price biddings on combinatorial auctions. In there, the combinatorial auction is extended to cover multi-unit scenario, which allows bidding for indistinguishable items to cover the case, for example, to assign an allocation of aggregated electricity in a day, considering electricity generation costs on the power suppliers. Although such a mechanism could be naively applied for dynamic electricity auctions and other various purposes, it is difficult to be applied for large-scale auction problems due to its computational intractability and theoretical limitations. In this paper, first a naive mechanism with reserve price bidding cannot be applied since it might violate the reserve price condition. Then, an extended pricing mechanism is introduced that employs an approximate allocation and pricing algorithm that is capable to handle multi-unit auctions with reserve price biddings, guaranteeing the reserve price condition. The algorithm is expected to efficiently produce approximation allocations that are necessary in pricing and it also behaves as an approximation of VCG(Vickrey-Clarke-Groves) mechanism satisfying budget balance condition and bidders' individual rationality without having single-minded bidders assumption.

[1]  M. Pipattanasomporn,et al.  Multi-agent systems in a distributed smart grid: Design and implementation , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[2]  Sarvapali D. Ramchurn,et al.  Agent-based control for decentralised demand side management in the smart grid , 2011, AAMAS.

[3]  Naoki Fukuta,et al.  An Approach to VCG-like Approximate Allocation and Pricing for Large-scale Multi-unit Combinatorial Auctions , 2013, J. Inf. Process..

[4]  Noam Nisan,et al.  Computationally feasible VCG mechanisms , 2000, EC '00.

[5]  Craig Boutilier,et al.  Solving Combinatorial Auctions Using Stochastic Local Search , 2000, AAAI/IAAI.

[6]  Takayuki Ito,et al.  An experimental analysis of biased parallel greedy approximation for combinatorial auctions , 2010, Int. J. Intell. Inf. Database Syst..

[7]  Takayuki Ito,et al.  Toward a Large Scale E-Market: A Greedy and Local Search Based Winner Determination , 2007, IEA/AIE.

[8]  Takayuki Ito,et al.  Toward Combinatorial Auction-based Better Electric Power Allocation on Sustainable Electric Power Systems , 2011, 2011 IEEE 13th Conference on Commerce and Enterprise Computing.

[9]  Y. Shoham,et al.  Truth revelation in rapid, approximately efficient combinatorial auctions , 2001 .

[10]  Takayuki Ito,et al.  Fine-grained efficient resource allocation using approximated combinatorial auctionsA parallel greedy winner approximation for large-scale problems , 2009, Web Intell. Agent Syst..

[11]  Naoki Fukuta,et al.  A Preliminary Implementation on Pricing Mechanisms for Electric Resource Control Markets , 2013, 2013 IEEE 6th International Conference on Service-Oriented Computing and Applications.

[12]  Noam Nisan,et al.  An efficient approximate allocation algorithm for combinatorial auctions , 2001, EC '01.

[13]  Yoav Shoham,et al.  Multiagent Systems - Algorithmic, Game-Theoretic, and Logical Foundations , 2009 .

[14]  David Levine,et al.  CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions , 2005, Manag. Sci..

[15]  William Drozd Automatically Defined Swarms for Task Allocation , 2007 .

[16]  Andrew B. Whinston,et al.  Solving the combinatorial double auction problem , 2005, Eur. J. Oper. Res..

[17]  Makoto Yokoo,et al.  Characterizing false-name-proof allocation rules in combinatorial auctions , 2009, AAMAS.

[18]  Takayuki Ito,et al.  A Preliminary Experimental Analysis on Combinatorial Auction-Based Electric Power Allocation for Manufacturing Industries , 2012, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[19]  Takayuki Ito,et al.  Towards Better Approximation of Winner Determination for Combinatorial Auctions with Large Number of Bids , 2006, 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

[20]  David J. C. MacKay Sustainable Energy - Without the Hot Air , 2008 .

[21]  Alex Rogers,et al.  A scoring rule-based mechanism for aggregate demand prediction in the smart grid , 2012, AAMAS.

[22]  Carmine Ventre,et al.  Mechanisms for multi-unit combinatorial auctions with a few distinct goods , 2013, AAMAS.

[23]  Yoav Shoham,et al.  Towards a universal test suite for combinatorial auction algorithms , 2000, EC '00.

[24]  Naoki Fukuta,et al.  Toward a VCG-Like Approximate Mechanism for Large-Scale Multi-unit Combinatorial Auctions , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[25]  Naoki Fukuta,et al.  A Market-Based Agent-Mediated Resource Control Framework for Middle-Scale Smart Grids , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[26]  Takayuki Ito,et al.  On implementing a market-based agent-mediated resource control framework for middle-scale smart grids: A preliminary study , 2012, 2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA).

[27]  Wei Li,et al.  A trust-incentive-based combinatorial double auction algorithm , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[28]  Jan T. Bialasiewicz,et al.  Power-Electronic Systems for the Grid Integration of Renewable Energy Sources: A Survey , 2006, IEEE Transactions on Industrial Electronics.