Coordinated Logistics with a Truck and a Drone

Carlsson, John Gunnar; Song, Siyuan

doi:10.1287/mnsc.2017.2824

Cited by 312 publications

(133 citation statements)

References 39 publications

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“…Carlsson and Song and Campbell et al use continuous approximation methods to derive analytical formulas for the expected delivery cost and times by assuming a continuous distribution of customer locations in 2D space. Campbell et al model truck travel with the L1 (Manhattan) metric and drone travel with the L2 (Euclidean) metric.…”

Section: Planning Combined Operations Of Drones With Other Vehiclesmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult‐to‐access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

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Section: Planning Combined Operations Of Drones With Other Vehiclesmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

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“…Most of this work utilizes coverage-based models, motivated by an assumed maximum distance that a bystander can travel to retrieve the AED before emergency responders arrive at the scene , Sun et al 2016). More recently, Chan et al (2018) The majority of this literature has focused on the problem of routing one or more drones in a coordinated fashion (Xia et al 2017) or on the flying sidekick travelling salesman problem, where a drone is routed in coordination with a traditional delivery vehicle (Murray and Chu 2015, Mourelo Ferrandez et al 2016, Dorling et al 2017, Carlsson and Song 2018, Agatz et al 2018.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing a Drone Network to Deliver Automated External Defibrillators

et al. 2017

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Background Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest (OHCA), but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an OHCA for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. Methods We applied our model to 53,702 OHCAs that occurred in the eight regions of the Toronto Regional RescuNET between January 1st 2006 and December 31st 2014. Our primary analysis quantified the drone network size required to deliver an AED one, two, or three minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as one large coordinated region. Results The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by three minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. Conclusion An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an OHCA event.

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“…Equation (6) ensures that a vehicle does not finish its trip at a task location and Equation (7) ensures that a vehicle does not finish its delivery trip at a start depot. Equation (8) states that all tasks should be served and Equation (9) links decision variables X ijkr and Y ikr .…”

Section: Mathematical Modelmentioning

confidence: 99%

“…There is no doubt that UAVs are more economical than the ground vehicles (GVs), as stated in previous literature [8]. Therefore, a variety of UAV logistic services, such as UAV only and truck-UAV hybrid services are emerging presently [9,10].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Investigation on the Sustainability of UAV Logistics

et al. 2019

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Unmanned aerial vehicles (UAVs) are expected to make groundbreaking changes in the logistics industry. Leading logistics companies have been developing and testing their usage of UAVs recently as an environmentally friendly and cost-effective option. In this paper, we investigate how much the UAV delivery service is environmentally friendly compared to the traditional ground vehicle (GV) delivery service. Since there are fuel (battery) and loadable weight restrictions in the UAV delivery, multi-hopping of UAV is necessary, which may cause a large consumption of electrical energy. We present a two-phase approach. In Phase I, a new vehicle routing model to obtain optimal delivery schedules for both UAV-alone and GV-alone delivery systems is proposed, which considers each system's restrictions, such as the max loadable weight and fuel replenishment. In Phase II, CO 2 emissions are computed as a sustainability measure based on the travelling distance of the optimal route obtained from Phase I, along with various GV travel-speeds. A case study finds that the UAV-alone delivery system is much more CO 2 efficient in all ranges of the GV speeds investigated.

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Coordinated Logistics with a Truck and a Drone

Cited by 312 publications

References 39 publications

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Optimizing a Drone Network to Deliver Automated External Defibrillators

Mathematical Investigation on the Sustainability of UAV Logistics

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