Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles

Savkin

2020

Sensors

This paper proposes a novel parcel delivery system which consists of a drone and public transportation vehicles such as trains, trams, etc. This system involves two delivery schemes: drone-direct scheme referring to delivering to a customer by a drone directly and drone–vehicle collaborating scheme referring to delivering a customer based on the collaboration of a drone and public transportation vehicles. The fundamental characteristics including the delivery time, energy consumption and battery recharging are modelled, based on which a time-dependent scheduling problem for a single drone is formulated. It is shown to be NP-complete and a dynamic programming-based exact algorithm is presented. Since its computational complexity is exponential with respect to the number of customers, a sub-optimal algorithm is further developed. This algorithm accounts the time for delivery and recharging, and it first schedules the customer which leads to the earliest return. Its computational complexity is also discussed. Moreover, extensive computer simulations are conducted to demonstrate the scheduling performance of the proposed algorithms and the impacts of several key system parameters are investigated.

Section: Simulation Resultsmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Scheduling of a Parcel Delivery System Consisting of an Aerial Drone Interacting with Public Transportation Vehicles

Savkin

2020

Sensors

“…Aside from commercial applications, such quantitative approaches can also be found in the humanitarian and disaster-related context. Drones are used for assessing infrastructure damage and last-mile logistics delivery of relief items to remote locations that are inaccessible for land-based transportation ( Mosterman et al, 2014 ; Scott and Scott, 2017 ; Chowdhury et al, 2017 ; Rabta et al, 2018 ; Golabi et al, 2017 ; Escribano Macias et al, 2020 ). Numerous papers have recently been published that put exclusive focus on drone delivery of critical emergency items such as automated external defibrillators (AEDs) for the treatment of people that suffer from sudden cardiac arrest ( Zègre-Hemsey et al, 2018 ; Pulver et al, 2016 ; Pulver and Wei, 2018 ; Boutilier et al, 2017 ).…”

Section: Related Literaturementioning

confidence: 99%

Containing the COVID-19 pandemic with drones - Feasibility of a drone enabled back-up transport system

Kunovjanek

Wankmüller

2021

Transport Policy

The COVID-19 pandemic has profoundly altered common social and economic patterns as governments all over the world have been forced to take drastic measures to counter the spread of the disease. Among them, quarantine, the closure of borders, and social distancing are the ones that have affected transportation systems most severely. With the clear need to avoid all unnecessary direct human contact, an increased interest in contactless transportation and delivery modes emerged. Drones are a promising alternative in this regard, especially for the delivery of essential goods, such as COVID-19 viral tests. In this study, we therefore investigate how drones can be used to distribute viral tests to potentially infected patients. The novel approach that we propose is to use existing drone infrastructure to perform this task, where drones owned and operated by different public and private entities are retrofitted for the distribution of essential goods in the case of emergency. In a wider sense, we hence suggest the establishment of a drone enabled back-up transport system. Potential performance gains are analyzed through a mathematical time and cost model that was developed in close cooperation with the state Red Cross Organization and a utility drone manufacturer. Process design as well as parameter estimation are based on empirical investigation including, but not limited to, accompanying a COVID-19 mobile testing team in the field. The practical feasibility was verified by retrofitting drones initially assigned to other purposes. Additionally, policy recommendations, such as the establishment of public-public and public-private partnerships, were identified.

Transportation Research Record: Journal of the Transportation R

“…Wen et al proposed a vehicle routing model that considers blood temperature variation based on the quantity of blood transported and length of each trip ( 24 ). Escribano Macias et al incorporated energy management and recharge to a location-routing algorithm for drone-based relief distribution ( 25 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, an aggregate value η has been used as the derivation of complex battery performance relationships is beyond the scope of this work. This value has been considered as appropriate as it has been previously used in the literature ( 16 , 25 ).…”

Section: Case Studymentioning

confidence: 99%

Design of Hospital Delivery Networks Using Unmanned Aerial Vehicles

Arenzana

Macias

Angeloudis

2020

Self Cite

Unmanned aerial vehicles (UAVs) are being increasingly implemented in a range of applications. Their low payload capacity and ability to overcome congested road networks enables them to provide fast delivery services for urgent high-value low-volume cargo. This work investigates the economic viability of integrating UAVs into urban hospital supply chains. In doing so, a strategic model that determines the optimal configuration of supporting infrastructure for urgent UAV delivery between hospitals is proposed. The model incorporates a tailored facility location algorithm that selects an optimal number of hubs given a set of candidates and determines the number of UAVs required to fulfill total demand. The objective is to minimize the total cost of implementation, computed as the sum of generalized, battery, vehicle, and hub establishment costs. The model is applied to a case study based on the establishment of a UAV delivery network for deliveries between National Health Service (NHS) hospitals in London. A baseline scenario is also developed using current NHS vehicles for delivery. Results demonstrate that UAV-based delivery provides significant reductions in operational costs compared with the baseline. Furthermore, the analysis indicates the location of hubs is more significant to the solution optimality than any increase in range or payload.