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.
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Bai, J., Chang, H., Yi, Y. (2005). An Immune Partheno-Genetic Algorithm for Winner Determination in Combinatorial Auctions. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_9
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DOI: https://doi.org/10.1007/11539902_9
Publisher Name: Springer, Berlin, Heidelberg
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