A decision support system to investigate dynamic last-mile distribution facilitating cargo-bikes
This work presents a decision support system to facilitate efficient urban last-mile distribution. Orders are collected and delivered by a fleet of both conventional vehicles owned by a logistics provider and cargo-bikes operated by freelancers. Additionally, micro-hubs are operated to perform transshipments between multiple vehicles. To investigate the corresponding problem setting, an agent-based simulation is developed, which uses dynamic optimisation procedures to generate and select vehicle routes and transshipment points. Experiments motivated by dynamic real-world urban restaurant delivery services investigate the impact of cargo-bikes, urban consolidation and guaranteed delivery times. Potentials are discussed and implications for successful implementations are provided. Results highlight the importance of having a sufficient number of active cargo-bikes available and benefits of incorporating consolidation strategies to guarantee timely deliveries.