Appointment scheduling and routing optimization of attended home delivery system with random customer behavior

Attended home delivery (AHD) has been identified as a crucial delivery mode of the last mile problem. As the name implies, AHD involves delivery of needed goods at the customer's doorsteps or nearby via walking or short-distance vehicle. Considering no-show and random response time, this article presents an integrative approach that combines appointment scheduling and vehicle routing problem with soft time windows. We also propose an intuitive heuristic dynamic programming to tackle the appointment scheduling problem whose optimal decision is expected to be very complicated, embed it into tabu search and formulate a hybrid heuristic algorithmto solve this integrative model. Moreover, an extension to hard time windows has also been discussed. Our results indicate that the integrative approach could lead to high-quality solutions in a reasonable amount of runtimeas compared to the hierarchical approach.

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