An optimization-driven dynamic vehicle routing algorithm for on-demand meal delivery using drones

•A mixed integer program (MIP) comprehensively characterizes the business operation of on-demand meal delivery service using drones.•An optimization-driven, rolling-horizon algorithm is developed to solve practical problem instances.•The temporally discrete, spatially continuous MIP formulation can...

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Veröffentlicht in:Computers & operations research Jg. 111; S. 1 - 20
1. Verfasser: Liu, Yanchao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Ltd 01.11.2019
Pergamon Press Inc
Schlagworte:
Algorithms
Business competition
Computer simulation
Constraint modelling
Delivery services
Drone delivery system
Drone vehicles
Dynamic vehicle routing
Formulations
Integer programming
Linear programming
Mixed integer
Mixed integer programming
Operations research
Optimization
Route planning
Transportation systems
Vehicle routing
Drone delivery system
Dynamic vehicle routing
Mixed integer programming
ISSN:0305-0548, 1873-765X, 0305-0548
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Zusammenfassung:•A mixed integer program (MIP) comprehensively characterizes the business operation of on-demand meal delivery service using drones.•An optimization-driven, rolling-horizon algorithm is developed to solve practical problem instances.•The temporally discrete, spatially continuous MIP formulation can handle dynamic vehicle routing scenarios with great flexibility.•The solutions are amenable to visualization and animation, therefore accessible for business users. As technology continues to improve people’s quality of life, there is a large, unfulfilled market worldwide for on-demand meal delivery services. The competitive edge of the business is foremost sharpened by the agility of the transport system. While lightweight drones are being developed as the next-generation vehicular platform for meal delivery, an efficient fleet operation becomes especially critical. This paper presents a mixed integer programming (MIP) model that comprehensively characterizes all relevant aspects of the business scenario, and proposes an optimization-driven, progressive algorithm for online fleet dispatch operations. Different from typical graph-based formulations of vehicle routing problems, the proposed temporally discrete and spatially continuous MIP formulation endogenously accounts for geometry and mobility and therefore permits dynamic input of order information with arbitrary pickup and delivery locations. The model is augmented with special constraints and an artificial objective function which effectively relay the system states between successive time horizons. The algorithm is validated through simulation case studies and is shown to meet the design objectives.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2019.05.024