Service Time Prediction for Last-Yard Delivery

Abstract

Service time is defined as the time taken for a courier to deliver a package to the doorstep of a customer after leaving his vehicle and includes the time taken to return back to his vehicle. Service time is a particularly important parameter in logistics job planning as together with travel time, they determine the number of jobs that can be planned for a day. Traditionally, logistics and transportation companies rely on planners to give a manual estimate of service time for different jobs. However, this process is time consuming and inaccurate. As such, a data-driven, automated Service Time Prediction (STP) method is proposed in this study to provide faster and more accurate service time predictions based on historical data. It does so by first determining historical service time from GPS data by detecting when a service is being conducted. Then, given the historical service times, a KNN regression model is used to provide predictions of service time for new jobs. This study was conducted using two sets of data from 2019 provided to us by two separate logistics and transportation companies based in Singapore. The type of goods delivered are FMCG products.