Abstract
Recently, the pickup and delivery problem has attracted increasing attention due to its applications in online food delivery services. At the same time, unforeseen events, such as vehicle breakdowns, traffic jam, and service time changes, often lead to the delay of delivery services. This paper defines the disruption recovery problem for the pickup and delivery problem with time windows (DR-PDPTW) and presents a scenario-based approach to solve the problem in a computationally efficient way. The approach starts with pre-disruption preparation that generates disruption scenarios and corresponding candidate recovery solutions. Once a disruption occurs, the approach will first check if recovery efforts are necessary based on the magnitude of delays caused by the disruption. If such delays are not acceptable, the approach will move to the post-disruption response stage to match the disruption with an already generated disruption scenario. Then corresponding candidate recovery solutions will be adjusted based on the actual disruption and executed. Computation experiments demonstrate the quality and efficiency of the proposed approach. This study can help to provide real-time decision support for disruption management in online food delivery services.
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