Crowd-shipping via Train Networks: Optimising Parcel Delivery by Part-timers and Commuters under Varying Occupancy Levels

Abstract

As urban areas seek sustainable delivery solutions, traditional road-based logistics face scrutiny for inefficiency and environmental impacts. In June 2024, Singapore Post and SMRT launched a trial using trains for postal collection during non-peak hours. This opens opportunities for crowd-shipping, where commuters deliver parcels while traveling. Existing research on crowd-shipping often overlooks variability in train occupancy levels, which can impact delivery feasibility. This study develops an optimisation model considering varying train occupancy levels, parcel capacity, and time window constraints for delivery assignments between crowd-shippers and part-timers. Additionally, it is the first to analyse Singapore Post's model of using part-time staff for mail collection via public transport. Findings show that using the train network reduces operational costs by 37.5% and greenhouse gas emissions by 97.9%, with further reductions achieved by combining part-timers and crowd-shippers. This research demonstrates the potential for a more sustainable, cost-effective urban logistics strategy using train-based crowd-shipping.