An immune partheno-genetic algorithm for winner determination in combinatorial auctions

Authors:
JianCong Bai;HuiYou Chang;Yang Yi
Affiliations:
Department of Computer Science, Sun Yat-sen University, GuangZhou, PRC;Department of Computer Science, Sun Yat-sen University, GuangZhou, PRC;Department of Computer Science, Sun Yat-sen University, GuangZhou, PRC
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

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Abstract

Combinatorial auctions are efficient mechanisms for allocating resource in complex marketplace. Winner determination, which is NP-complete, is the core problem in combinatorial auctions. This paper proposes an immune partheno-genetic algorithm (IPGA) for solving this problem. Firstly, a zero-one programming model is built for the winner determination problem with XOR-bids and OR-bids. Then, steps of constructing three partheno-genetic operators and an immune operator are introduced. In the immune operation, new heuristics are designed for vaccines selection and vaccination. Simulation results show that the IPGA achieves good performance in large size problems and the immune operator can improve the searching ability and increase the converging speed greatly.