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

Ming Liu, Xin Liu, Maoran Zhu and Feifeng Zheng
Additional contact information
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

Sustainability, 2019, vol. 11, issue 14, 1-18

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.

Keywords: drone; fleet deployment; service module; parcel delivery (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/14/3871/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/14/3871/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:14:p:3871-:d:248916

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().