The second-hand goods exchange matching problem with intelligent exchange platform is a valuable research topic, while research in the related field is relatively lacking. Thus, the goal of this paper is to develop a two-sided matching method for the second-hand goods exchange matching. In the method, not only the characteristic of loss aversion of buyers/sellers and the benefit of e-brokerage are considered, but also the suggested exchange prices that meet the requirements of buyers and sellers are determined. Specifically, the description of second-hand goods exchange matching problem is firstly presented, in which the 2-tuple including the ideal level and the lowest acceptable level is used to quantify the expected demands of buyers and sellers for attributes. Then, several models maximizing the perceived values of buyers and sellers are derived to determine the suggested exchange price of goods. Next, according to the expectation information of buyers and sellers, and the real information of goods, the perceived value matrix for each attribute of buyers and sellers can be obtained by using the prospect theory. Furthermore, a model can be constructed and solved to determine the maximum number of exchange of buyers and sellers in e-brokerage, and an optimization model with the constraint of the exchange number threshold is constructed, and the optimal exchange matching results can be obtained by solving the optimization model. Finally, an example is given to illustrate the practicality of the proposed method. The method can be used to improve the operational performance of intelligent exchange platforms.

智能交易平台上的二手商品交易匹配问题是一个有价值的研究课题，而相关领域的研究相对缺乏。因此，本文的目的是开发一种用于二手商品交换匹配的双面匹配方法。该方法不仅考虑了买卖双方的损失厌恶特性和电子经纪业务的利益，而且还确定了符合买卖双方要求的建议汇率。具体而言，首先给出了二手商品交换匹配问题的描述，其中使用包括理想水平和最低可接受水平的二元组来量化买卖双方对属性的期望需求。然后，推导了一些最大化买卖双方感知价值的模型，以确定商品的建议交易价格。其次，根据买卖双方的期望信息和商品的真实信息，可以利用前景理论获得买卖双方各属性的感知价值矩阵。此外，可以建立并求解模型来确定电子经纪中买卖双方的最大交易数量，并构造一个具有交易数量阈值约束的优化模型，并通过以下方法获得最优的交易匹配结果：解决优化模型。最后，通过算例说明了该方法的实用性。该方法可用于提高智能交易平台的运行性能。