The truck and drone-based cooperative model of delivery can improve the efficiency of last mile delivery, and has thus increasingly attracted attention in academia and from practitioners. In this study, we examine a vehicle routing problem and apply a cooperative form of delivery involving trucks and drones. We propose a mixed-integer programming model and a branch-price-and-cut-based exact algorithm to address this problem. To reduce the computation time, we design several acceleration strategies, including a combination of dynamic programming and calculus-based approximation for the pricing problem, and various effective inequalities for the restricted master problem. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed solution.

Zhen, L., Gao, J., Tan, Z., Wang, S., Baldacci, R. (2023). Branch-price-and-cut for trucks and drones cooperative delivery. IISE TRANSACTIONS, 55(3), 271-287 [10.1080/24725854.2022.2060535].

Branch-price-and-cut for trucks and drones cooperative delivery

Wang S.;Baldacci R.
2023

Abstract

The truck and drone-based cooperative model of delivery can improve the efficiency of last mile delivery, and has thus increasingly attracted attention in academia and from practitioners. In this study, we examine a vehicle routing problem and apply a cooperative form of delivery involving trucks and drones. We propose a mixed-integer programming model and a branch-price-and-cut-based exact algorithm to address this problem. To reduce the computation time, we design several acceleration strategies, including a combination of dynamic programming and calculus-based approximation for the pricing problem, and various effective inequalities for the restricted master problem. Numerical experiments are conducted to validate the effectiveness and efficiency of the proposed solution.
2023
Zhen, L., Gao, J., Tan, Z., Wang, S., Baldacci, R. (2023). Branch-price-and-cut for trucks and drones cooperative delivery. IISE TRANSACTIONS, 55(3), 271-287 [10.1080/24725854.2022.2060535].
Zhen, L.; Gao, J.; Tan, Z.; Wang, S.; Baldacci, R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/897416
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