An algorithm for computing the outcome of combinatorial auctions with proxy bidding
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
Robust solutions for combinatorial auctions
Proceedings of the 6th ACM conference on Electronic commerce
Performance Analysis about Parallel Greedy Approximation on Combinatorial Auctions
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
An experimental analysis of biased parallel greedy approximation for combinatorial auctions
International Journal of Intelligent Information and Database Systems
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Despite the large amounts of runtime needed to adequately solve a combinatorial auction (CA), existing iterative CA auction protocols require winner determination during every round of bid submissions. Using existing algorithms for winner determination will cause a timing bottleneck during the winner determination phase. Furthermore, there has recently been work which models the formation of supply chains through auctions. Here, winner determination is used for supply chain formation. As supply chains become more dynamic, there is a need for incremental algorithms that quickly and accurately restructure the supply chain while keeping the initial supplier/producer/consumer constraints satisfied.In this work, we look into the process of quickly and efficiently handling incremental changes in combinatorial auctions. Given some perturbations, we illustrate the trade off between preserving the previous solution while maximizing the valuation of the auction. Our results show that it is possible to use a locally optimal solution while sacrificing little solution quality compared to a globally optimal solution. When we have 5000 bids or more, the local algorithm gives a solution within 2% of optimal on the "matching" benchmark from the Combinatorial Auction Test Suite (CATS). Therefore, a simple, fast algorithm can be used to handle incremental changes in CAs with a large number of bids.