Matching model and algorithm for multi-unit multi-attribute exchanges with fuzzy information in E-brokerage
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    Abstract:

    With respect to the fuzzy information of multi-unit multi-attribute exchanges in E-brokerage,this paper employs fuzzy set theory to represent the traders’orders with fuzzy information and proposes a new calculation method of matching degree based on the improved fuzzy information axiom from both the buyers’and sellers’points of view. Afterward,a mathematic model is built to maximize the matching degree and the trade quantity,and the model belongs to a class of nonlinear multi-objective transportation problems.According to the complexity and characteristics of the model,a multi-objective discrete differential evolution with Prüfer-encoding is developed to solve it.The model is useful and the algorithm is effective,which is verified by the simulation experiment and results analysis.

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  • Online: April 16,2018
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