Towards Comprehensive Bidder Support in Online Combinatorial Auctions

Many auctions involve selling several distinct items simultaneously, where bidders can bid on the whole or any part of the lot. Such auctions are referred to as combinatorial auctions. Examples of such auctions include truck delivery routes, furniture, and FCC spectrum. Determining winners in such auctions is an NP-hard problem and significant research is being conducted in this area. However, multiple round (iterative) combinatorial auctions present significant challenges in bid formulations as well. Since the combinatorial dynamics in iterative auctions can make a given bid a part of winning and non-winning set of bids without any changes in the bid, bidders are usually not able to evaluate whether they should revise their bid at a given point in time or not. Therefore, in this paper we address various computational problems that are relevant from the bidder’s perspective. In particular, we introduce several bid evaluation metrics that can be used by bidders to determine whether any given bid can be a part of the winning allocation and explored their theoretical properties. Based on these metrics, we also developed efficient data structures and algorithms that provide comprehensive information about the current auction state to bidders at any auction stage, which can help bidders in evaluating their bids and bidding strategies. The performance analysis suggests that the proposed approach is suitable for real-time bidder support. * Alok Gupta’s research is supported by NSF Career grant #IIS-0301239 but does not necessarily reflect the views of the NSF.