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Stochastic Drone Fleet Deployment and Planning Problem Considering Multiple-Type Delivery Service

Author

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  • Ming Liu

    (School of Economics & Management, Tongji University, Shanghai 200092, China)

  • Xin Liu

    (School of Economics & Management, Tongji University, Shanghai 200092, China)

  • Maoran Zhu

    (School of Economics & Management, Tongji University, Shanghai 200092, China)

  • Feifeng Zheng

    (Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China)

Abstract

Drone delivery has a great potential to change the traditional parcel delivery service in consideration of cost reduction, resource conservation, and environmental protection. This paper introduces a novel drone fleet deployment and planning problem with uncertain delivery demand, where the delivery routes are fixed and couriers work in collaboration with drones to deliver surplus parcels with a relatively higher labor cost. The problem involves the following two-stage decision process: (i) The first stage determines the drone fleet deployment (i.e., the numbers and types of drones) and the drone delivery service module (i.e., the time segment between two consecutive departures) on a tactical level, and (ii) the second stage decides the numbers of parcels delivered by drones and couriers on an operational level. The purpose is to minimize the total cost, including (i) drone deployment and operating cost and (ii) expected labor cost. For the problem, a two-stage stochastic programming formulation is proposed. A classic sample average approximation method is first applied. To achieve computational efficiency, a hybrid genetic algorithm is further developed. The computational results show the efficiency of the proposed approaches.

Suggested Citation

  • Ming Liu & Xin Liu & Maoran Zhu & Feifeng Zheng, 2019. "Stochastic Drone Fleet Deployment and Planning Problem Considering Multiple-Type Delivery Service," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:14:p:3871-:d:248916
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    References listed on IDEAS

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    Cited by:

    1. Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    2. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    3. Grzegorz Radzki & Izabela Nielsen & Paulina Golińska-Dawson & Grzegorz Bocewicz & Zbigniew Banaszak, 2021. "Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments," Sustainability, MDPI, vol. 13(9), pages 1-23, May.
    4. Kaiping Wang & Mingzhu Song & Meng Li, 2021. "Cooperative Multi-UAV Conflict Avoidance Planning in a Complex Urban Environment," Sustainability, MDPI, vol. 13(12), pages 1-21, June.

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