Abstract
Mixed multi-unit combinatorial auctions (MMUCAs) offer a high potential to be employed for the automated assembly of supply chains of agents. However, in order for mixed auctions to be effectively applied to supply chain formation, we must ensure computational tractability and reduce bidders' uncertainty. With this aim, we introduce Sequential Mixed Auctions (SMAs), a novel auction model conceived to help bidders collaboratively discover supply chain structures. Thus, an SMA allows bidders progressively build a supply chain structure through successive auction rounds. Moreover, the incremental nature of an SMA provides its participants with valuable information at the end of each auction round to guide their bidding. Finally, we empirically show that SMAs significantly reduce the computational effort required by MMUCA at the expense of a slight decrease in the auctioneer's revenue.
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