Abstract: To solve the problem of traceability data missing, out of sync or incompleteness in food traceability, an intelligent traceability method was proposed which used the turnaround time of traceability units to estimate units'flowing state and path. In this method, the turnaround time of a traceability unit between two nodes in the food chain network was taken as a continuous random variable to estimate the turnaround time distribution by using historical data route. The path estimation optimization model was established by taking mathematical expectation of traceability units'turnaround time distribution between nodes as variables and the minimum between the total time of the path and a given time as the optimization goal. The Monte Carlo simulation was used to simulate the time distribution of the flowing path to verify the feasibility of the estimated path. The simulation results showed that the proposed method did not depend on the traceability unit synchronization information. The flow state of the traceability unit might be predicted in the food chain network, as only the sent node was known. The historical flow path of the traceability unit might be estimated by giving the sent node and the terminal node.

Key words: food traceability|traceability units|Monte Carlo simulation|radio frequency identification|optimization model

摘要： 为了解决食品追溯过程中存在的追溯数据缺失、不同步或不完备的问题，提出利用追溯单元流转时间预测其流动状态、估测其历史流动路径的智能化追溯方法。该方法将追溯单元在食品链网络中两节点间流转的时间看作连续随机变量，利用历史数据估计流转时间的分布特征；以节点间是否存在追溯单元流转及其流转时间分布的数学期望为变量，以两节点间路径总时间与给定时间的差值最小为最优化目标，建立路径估测优化模型，并采用Monte Carlo仿真对估测路径的时间分布进行模拟，验证追溯单元流动路径的可行性。仿真结果表明，该方法不依赖于追溯单元的同步信息，可在仅已知追溯单元发出节点的情况下，预测追溯单元在食品链网络中的流动状态，在已知追溯单元发出节点和终端节点时估测其历史流动路径。

关键词: 食品追溯|追溯单元|Monte Carlo仿真|无线射频识别|优化模型