A graphical formalism for mixed multi-unit combinatorial auctions

Mixed multi-unit combinatorial auctions are auctions that allow participants to bid for bundles of goods to buy, for bundles of goods to sell, and for transformations of goods. The intuitive meaning of a bid for a transformation is that the bidder is offering to produce a set of output goods after having received a set of input goods. To solve such an auction the auctioneer has to choose a set of bids to accept and decide on a sequence in which to implement the associated transformations. Mixed auctions can potentially be employed for the automated assembly of supply chains of agents. However, mixed auctions can be effectively applied only if we can also ensure their computational feasibility without jeopardising optimality. To this end, we propose a graphical formalism, based on Petri nets, that facilitates the compact represention of both the search space and the solutions associated with the winner determination problem for mixed auctions. This approach allows us to dramatically reduce the number of decision variables required for solving a broad class of mixed auction winner determination problems. An additional major benefit of our graphical formalism is that it provides new ways to formally analyse the structural and behavioural properties of mixed auctions. © 2009 Springer Science+Business Media, LLC.This work was funded by the Jose Castillejo programme (JC2008-00337), IEA (TIN2006-15662-C02-01), OK (IST-4-027253-STP), eREP(EC-FP6-CIT5-28575) and Agreement Technologies (CONSOLIDER CSD2007-0022, INGENIO 2010)Peer Reviewe

Noname manuscript No. (will be inserted by the editor) A Graphical Formalism for Mixed Multi-Unit Combinatorial Auctions

Abstract Mixed Multi-Unit Combinatorial Auctions are auctions that allow participants to bid for bundles of goods to buy, for bundles of goods to sell, and for transformations of goods. The intuitive meaning of a bid for a transformation is that the bidder is offering to produce a set of output goods after having received a set of input goods. To solve such an auction the auctioneer has to choose a set of bids to accept and decide on a sequence in which to implement the associated transformations. Mixed auctions can potentially be employed for the automated assembly of supply chains of agents. However, mixed auctions can be effectively applied only if we can also ensure their computational feasibility without jeopardising optimality. To this end, we propose a graphical formalism, based on Petri nets, that facilitates the compact represention of both the search space and the solutions associated with the winner determination problem for mixed auctions. This approach allows us to dramatically reduce the number of decision variables required for solving a broad class of mixed auction winner determination problems. An additional major benefit of our graphical formalism is tha