Decision support for multi-attribute auctions

Karakaya, Gülşah
In this study, we address multi-attribute, multi-item auction problems. In multi-attribute auctions there are additional attributes to the price and the comparison of bids is not straightforward. In multi-item auctions which are also known as combinatorial auctions, it is not so trivial to determine the winning bidders. We develop an auction decision support system (ADSS) that supports sellers to bid on multiple items. We demonstrate our approach in a multi-attribute, multi-item reverse auction setting. The approach is also directly applicable to forward auctions. During the auction process, ADSS estimates the underlying preference function of the buyer and supports sellers providing them information based on these estimations. We first assume that the sellers do not share their cost functions with ADSS and develop interactive algorithms for underlying linear preference functions as well as for underlying quasiconvex preference functions. The aim of the developed approaches is to have the more competitive bidders eventually end up winning the auction, with predetermined reasonable mark-up values. We demonstrate that our algorithms work well on a variety of test problems. We also develop an interactive algorithm for the case that sellers explicitly make their cost functions available to ADSS. In this approach, ADSS tries to find the best possible combinations considering both the estimated preference function of the buyer and the cost functions of the sellers. The experiments show that our algorithm finds the optimal winners (achieved with exact parameters of the underlying preference function).
Citation Formats
G. Karakaya, “Decision support for multi-attribute auctions,” Ph.D. - Doctoral Program, Middle East Technical University, 2013.