Computationally Manageable Combinational Auctions
Management Science
On the run-time behaviour of stochastic local search algorithms for SAT
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Truth revelation in approximately efficient combinatorial auctions
Proceedings of the 1st ACM conference on Electronic commerce
Combinatorial auctions for supply chain formation
Proceedings of the 2nd ACM conference on Electronic commerce
Solving Combinatorial Auctions Using Stochastic Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Integer Programming for Combinatorial Auction Winner Determination
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Costly valuation computation in auctions
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
Combinatorial Auction-Based Protocols for Resource Allocation in Grids
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 13 - Volume 14
Customer-Driven Sensor Management
IEEE Intelligent Systems
Multi-agent systems for data-rich, information-poor environments
Multi-agent systems for data-rich, information-poor environments
Combinatorial auctions with k-wise dependent valuations
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
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
A q-learning based adaptive bidding strategy in combinatorial auctions
Proceedings of the 11th International Conference on Electronic Commerce
An experimental analysis of biased parallel greedy approximation for combinatorial auctions
International Journal of Intelligent Information and Database Systems
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Combinatorial Auctions (CAs), where users bid on combination of items, have emerged as a useful tool for resource allocation in distributed systems. However, two main difficulties exist to the adoption of CAs in time-constrained environments. The first difficulty involves the computational complexity of winner determination. The second difficulty entails the computational complexity of eliciting utility valuations for all possible combinations of resources to different tasks. To address both issues, we developed a new algorithm, Seeded Genetic Algorithm (SGA) for finding high quality solutions quickly. SGA uses a novel representational schema that produces only feasible solutions. We compare the winner determination performance of our algorithm with Casanova, another local stochastic search procedure, on typically hard-to-solve bid distributions. We show that SGA converges to a better solution than Casanova for large problem sizes. However, for many bid distributions, exact winner determination using integer programming approaches is very fast, even for large problem sizes. In these cases, SGA can still provide significant time savings by eliminating the requirement for formulating all possible bids.