Integrated routing for a vehicle-robot pickup and delivery system with time constraints

TL;DR

This paper models an integrated vehicle-robot routing problem with time constraints as a MIQCP, optimizing routes to minimize total tardiness, and demonstrates its effectiveness through computational experiments.

Contribution

It formulates the vehicle-robot pickup and delivery routing as a MIQCP, addressing the integrated routing problem with time constraints for the first time.

Findings

The MIQCP model effectively minimizes total tardiness.

Gurobi solver successfully solves small and medium instances.

The approach is practical for real-world delivery systems.

Abstract

This paper considers an unmanned vehicle-robot pickup and delivery system, in which a self-driving vehicle carrying multiple unmanned robots in the form of the mother ship travels from a depot to a number of stations distributed in a neighborhood to perform multiple pickup and delivery services. First of all, we present it as a Multi-modal Vehicle Routing Problem (MMVRP) with time constraints, which are typical service requirements for grocery and food delivery in practice. We then formulate it as a Mixed Integer Quadratically Con-strained Program (MIQCP) model to determine the optimal integrated routing plan (vehicle routing and robot routing) to minimize the total weighted tardiness of all services. Finally, a small-size and a medium-size problem instance are solved using the Gurobi solver in Python to demonstrate the validity and the performance of the proposed MIQCP model.