The pickup and delivery problem with multiple depots and dynamic occasional drivers in crowdshipping delivery

In recent years, crowdshipping has gained much popularity because it not only has economic and environmental advantages, but also is regarded as an effective way to increase the resilience of supply chains and logistics. In this work, we focus on a last-mile delivery system that supports its O2O e-commerce partner for processing and fulfilling online orders in an urban area. Besides the full-time regular drivers, the system also relies on occasional drivers from society who dynamically announce their availability over the time horizon. We model the studied problem as a multi-depot pickup and delivery problem with dynamic occasional drivers. An event-based rolling horizon solution approach is proposed to solve the problem through iteratively calling for a re-optimization procedure to update the delivery plan at each decision epoch. Besides, we investigate the scenarios of disruptions to the delivery system. Extensive numerical experiments have proven the effectiveness of our proposed approach and have also demonstrated the studied crowdshipping system can help achieve the supply chain and logistics resilience. Moreover, sensitivity analysis on several important parameters have been carried out and managerial insights are drawn.