Kriging Method-Based Return Prediction of Waste Electrical and Electronic Equipment in Reverse Logistics

In reverse logistics, the accurate prediction of waste electrical and electronic equipment (WEEE) return amount is of great significance to guide electronic enterprises to formulate a reasonable recycling plan, remanufacturing production plan and inventory plan. However, due to the uncertainty of WEEE return, it is a challenge to accurately predict the WEEE return amount of recycling sites. Differently from the existing research methods aiming at the spatial correlation of the recycling amount of recycling sites, a spatial mathematical model based on Kriging method is proposed by this paper to predict the return amount of WEEE in reverse logistics. Based on the second-order randomness of the return amount, the spatial structure of the return amount of the recycling network is analyzed. According to the principle of unbiased prediction and minimum variance, the Kriging space mathematical model of WEEE return amount is derived, and the calculation process of three variograms is given. The results of Monte Carlo simulation and the case study on J company in Shanghai show that it is effective to utilize the Kriging method-based spatial mathematical model to predict the WEEE return of reverse logistics and analyze the spatial correlation structure of each recycling site. The proposed model can accurately predict the WEEE return amounts of unknown sites as well as those of the whole area through the known site data, which provides a novel analysis method and theoretical basis for the prediction of reverse logistics return amount.

Automated summary

This paper presents a spatial mathematical model based on the Kriging method for predicting the return amount of WEEE in reverse logistics. Through spatial structure analysis and Monte Carlo simulation, the effectiveness of the model is demonstrated.