1. Decision Support for Multiple-Unit Combinatorial Auctions Seminar 5.12.07
Riikka-Leena Leskelä
Supervisors: Hannele and Jyrki Wallenius

2. Background What has been done
Computational aspects of combinatorial auctions
Design of iterative (efficient) auction mechanisms – price feedback
Preference elicitation
What has not been done
Support for bidders in constructing new bids
Especially in the multiple-unit setting, which usually ignored – price and quantity feedback

3. Research Design of the Quantity Support Mechanism
An MILP solving for profit maximizing bids (q’s and p) that team up with other bids to become winners
Testing the QSM with simulations
Final cost to the buyer
Efficiency of the final allocation

4. Main Findings
QSM decreases total cost to buyer and improves efficiency
Shortcoming: QSM solves for one new bid at a time
It won’t suggest a good bid, if complements for the bid are not in the bid stream already

5. Conclusion Provide ”quantity support” for bidders Next:
not considered in previous literature
Next:
Extending QSM for groups of bidders to overcome the problems caused by considering only one incoming bid at a time
Testing with human subjects

6. Key References Good review of combinatorial auctions:
Pekeč and Rothkopf (2003), Combinatorial Auction Design, Management Science 49:
About the Quantity Support Mechanism:
Leskelä, Teich, Wallenius H. and Wallenius J. (2007), Decision Support for Combinatorial Bundle Auctions, Decision Support Systems 43: