Optimization of battery swapping infrastructure for e-commerce drone delivery

Cokyasar, Taner

doi:10.1016/j.comcom.2020.12.015

Cited by 48 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Asadi and Pinkley (2021) studied scheduling, allocation and inventory replenishment at battery swap stations to overcome battery degradation for drones and electric vehicles. Cokyasar (2021) introduced automated battery swapping machines (ABSMs) to the design of a drone-based service network, which is greatly promoted by the United States government. Although introduction of these facilities can extend the service time of a drone, some important issues have been identified and remain unaddressed.…”

Section: Drone Routing and Operation Optimisationmentioning

confidence: 99%

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

et al. 2021

View full text Add to dashboard Cite

Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.

show abstract

Section: Drone Routing and Operation Optimisationmentioning

confidence: 99%

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

et al. 2021

View full text Add to dashboard Cite

show abstract

“…However, in the last few years, drones' capability has prospered and is now capable of accomplishing multiple and simultaneous functions. Such capabilities are aerial photography [37], shipping and delivery [38][39][40], data collection [41,42], search and rescue operations during disasters or calamities [43], agricultural crop monitoring [44], natural calamity monitoring, and tracking [45]. UAVs were also successfully integrated into marine science and conservation.…”

Section: Aquaculture's Technological Innovation For Precision Farmingmentioning

confidence: 99%

A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management

Ubina

Cheng

2022

Drones

View full text Add to dashboard Cite

This paper aims to provide an overview of the capabilities of unmanned systems to monitor and manage aquaculture farms that support precision aquaculture using the Internet of Things. The locations of aquaculture farms are diverse, which is a big challenge on accessibility. For offshore fish cages, there is a difficulty and risk in the continuous monitoring considering the presence of waves, water currents, and other underwater environmental factors. Aquaculture farm management and surveillance operations require collecting data on water quality, water pollutants, water temperature, fish behavior, and current/wave velocity, which requires tremendous labor cost, and effort. Unmanned vehicle technologies provide greater efficiency and accuracy to execute these functions. They are even capable of cage detection and illegal fishing surveillance when equipped with sensors and other technologies. Additionally, to provide a more large-scale scope, this document explores the capacity of unmanned vehicles as a communication gateway to facilitate offshore cages equipped with robust, low-cost sensors capable of underwater and in-air wireless connectivity. The capabilities of existing commercial systems, the Internet of Things, and artificial intelligence combined with drones are also presented to provide a precise aquaculture framework.

show abstract

“…A heuristic algorithm is presented for the setting where the feasible positions of charging stations are given by a discretised set. The work in [ 28 ] considers a similar problem, but the objective is to minimise the total system cost, including the charging stations, UAV ownership, service congestion, etc. In a different approach to [ 27 , 28 ], the paper [ 29 ] considers the deployment of charging stations in a continuous space, and a decentralised method is presented which can achieve the locally optimal coverage of customers.…”

Section: Related Workmentioning

confidence: 99%

“…The work in [ 28 ] considers a similar problem, but the objective is to minimise the total system cost, including the charging stations, UAV ownership, service congestion, etc. In a different approach to [ 27 , 28 ], the paper [ 29 ] considers the deployment of charging stations in a continuous space, and a decentralised method is presented which can achieve the locally optimal coverage of customers. Targeting the application of inspecting a given set of sites, the reference [ 30 ] considers deploying charging stations at some sites so that a UAV can complete all the inspection tasks using the smallest amount of time; the authors additionally pay attention to the route planning problem for the UAV.…”

Section: Related Workmentioning

confidence: 99%

Optimal Deployment of Charging Stations for Aerial Surveillance by UAVs with the Assistance of Public Transportation Vehicles

Huang

Savkin

2021

Sensors

View full text Add to dashboard Cite

To overcome the limitation in flight time and enable unmanned aerial vehicles (UAVs) to survey remote sites of interest, this paper investigates an approach involving the collaboration with public transportation vehicles (PTVs) and the deployment of charging stations. In particular, the focus of this paper is on the deployment of charging stations. In this approach, a UAV first travels with some PTVs, and then flies through some charging stations to reach remote sites. While the travel time with PTVs can be estimated by the Monte Carlo method to accommodate various uncertainties, we propose a new coverage model to compute the travel time taken for UAVs to reach the sites. With this model, we formulate the optimal deployment problem with the goal of minimising the average travel time of UAVs from the depot to the sites, which can be regarded as a reflection of the quality of surveillance (QoS) (the shorter the better). We then propose an iterative algorithm to place the charging stations. We show that this algorithm ensures that any movement of a charging station leads to a decrease in the average travel time of UAVs. To demonstrate the effectiveness of the proposed method, we make a comparison with a baseline method. The results show that the proposed model can more accurately estimate the travel time than the most commonly used model, and the proposed algorithm can relocate the charging stations to achieve a lower flight distance than the baseline method.

show abstract

Optimization of battery swapping infrastructure for e-commerce drone delivery

Cited by 48 publications

References 23 publications

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management

Optimal Deployment of Charging Stations for Aerial Surveillance by UAVs with the Assistance of Public Transportation Vehicles

Contact Info

Product

Resources

About