Abstract：By easing the consistency hypothesis of alternative or complementary auction items for bidders, this paper establishes a combinational auction model according to bidders' bid on the basis of combinatorial auction mechanism design. In order to efficiently obtain the optimal allocation of multiple items, particle swarm optimization (PSO) algorithm is used to simulate the optimization process of allocation, and then the combinatorial auction model based on PSO algorithm is constructed. The paper designs and implements the combinatorial auction model based on PSO algorithm on swarm simulation platform, and verifies the simulation validation through a specific combinational auction example. The analysis of simulation results shows that the combinatorial auction model based on PSO algorithm can effectively solve the problem of the distribution of multiple items, and can maximize the benefit of the vendor. The parameter analysis of learning ability shows that compared with self-learning ability, social learning ability is more important to the optimization of seller's return. This paper will have certain reference value to both the theoretical research and practical application of combinatorial auction.
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2016, Vol. 36 
