Prediction of B2C e-commerce order arrival using hybrid autoregressive-adaptive neuro-fuzzy inference system (AR-ANFIS) for managing fluctuation of throughput in e-fulfilment centres

作者：

Highlights：

• A new study that forecasts the daily arrival pattern of e-commerce orders.

• An AR-ANFIS model for e-order arrival prediction is proposed.

• A two-stage model performance validation is introduced.

• Experimental results indicate that the proposed model outperforms ARIMA model.

摘要

•A new study that forecasts the daily arrival pattern of e-commerce orders.•An AR-ANFIS model for e-order arrival prediction is proposed.•A two-stage model performance validation is introduced.•Experimental results indicate that the proposed model outperforms ARIMA model.

论文关键词：E-commerce logistics,Order arrival prediction,Warehouse postponement applications,Adaptive neuro-fuzzy inference system (ANFIS),Autoregressive (AR) model

论文评审过程：Received 20 August 2018, Revised 14 May 2019, Accepted 20 May 2019, Available online 21 May 2019, Version of Record 20 June 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.027