A vehicle-UAV operation scheme for instant delivery

Gu, Qiuchen; Fan, Tijun; Pan, Fei; Zhang, Chong

doi:10.1016/j.cie.2020.106809

Cited by 50 publications

(31 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gschwind [28] and Azi [29] developed a large neighborhood search heuristic to optimize the pickup and delivery problem. Gu [30] presented the benefits of the truck-drone combination associated with the ordering takeout delivery of two advanced ant colony heuristics and a method to minimize the number of dispatched vehicles and the total travel time. Besides, the same-day delivery is another subtopic of research worthy of attention.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Rider Scheduling for a Food Delivery Service in O2O Business

Xue

Wang

2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

Services such as Meituan and Uber Eats have revolutionized the way the customer can find and order from restaurants. Numerous independent restaurants are competing for orders placed by customers via online food ordering platforms. Ordering takeout food on smartphone apps has become more and more prevalent in recent years. There are some operational challenges that takeout food service providers have to deal with, e.g., customer demand fluctuates over time and region. In this sense, the service providers sometimes ignore the fact that some riders may be idle in several periods in regions, while, in contrast, there may be a shortage of riders in other situations. In order to address this problem, we introduce a two-stage model to optimize scheduling of riders for instant food deliveries. A service provider platform expectantly schedules the least quantity of riders to deliver within expected arrival time to satisfy customer demand in different regions and time periods. We introduce a two-stage model that adopts the method of mixed-integer programming (MIP), characterize relevant aspects of the scenario, and propose an optimization algorithm for scheduling riders. We also divide the delivery service region and time into smaller parts in terms of granularity. The large neighborhood search algorithm is validated through numerical experiments and is shown to meet the design objectives. Furthermore, this study reveals that the optimization of rider resource is beneficial to reduce overall cost of the delivery. Takeout food service platforms decide scheduling shifts (start time and duration) of the riders to achieve a service level target at minimum cost. Additional sensitivity analyses, such as the tightness of the order time windows associated with the orders and riders’ familiarity with delivery regions, are also discussed

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Rider Scheduling for a Food Delivery Service in O2O Business

Xue

Wang

2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…In addition, a shift-weights process was added to the selection of vehicle stops to shorten the total delivery time. Gu et al [7] considered the scenario of multiple vehicles carrying multiple drones and determined the location of the vehicle stopping point, the assignment of customers, the assignment of UAVs, and the route of the vehicles by building two models and solved the problem with two improved ant colony optimizations (ACOs). Bakir et al [31] put the problem as a mixed-integer linear program on a time-space network and presented an efficient optimization algorithm based on a dynamic discretization discovery approach.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (6) indicates that the UAVs' service time includes the UAVs' in-transit operation time and the stay time at the customer points where t s is the service time of a single customer. Constraint (7) is the energy consumption constraint of the UAV line where E max is the total energy of the UAV. Constraint ( 8) is the load constraint of the UAV line.…”

Section: Uav Task Assignment Modelmentioning

confidence: 99%

See 1 more Smart Citation

Vehicle-Assisted UAV Delivery Scheme Considering Energy Consumption for Instant Delivery

Deng

Guan

et al. 2022

Sensors

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are increasingly used in instant delivery scenarios. The combined delivery of vehicles and UAVs has many advantages compared to their respective separate delivery, which can greatly improve delivery efficiency. Although a few studies in the literature have explored the issue of vehicle-assisted UAV delivery, we did not find any studies on the scenario of an UAV serving several customers. This study aims to design a new vehicle-assisted UAV delivery solution that allows UAVs to serve multiple customers in a single take-off and takes energy consumption into account. A multi-UAV task allocation model and a vehicle path planning model were established to determine the task allocation of the UAVs as well as the path of UAVs and the vehicle, respectively. The model also considered the impact of changing the payload of the UAV on energy consumption, bringing the results closer to reality. Finally, a hybrid heuristic algorithm based on an improved K-means algorithm and ant colony optimization (ACO) was proposed to solve the problem, and the effectiveness of the scheme was proven by multi-scale experimental instances and comparative experiments.

show abstract

“…However, there exists operation and acquisition process confusion resulting from manual operation of the drones for transmission line inspection. Besides, the drones suffer the disadvantages of poor long-distance maneuverability and short battery life [7] . In order to solve the above problems, some power companies launched a new type of power inspection operation mode of "UAV and operating vehicle (OV)".…”

Section: Introductionmentioning

confidence: 99%

The Collaborative Power Inspection Task Allocation Method of “Unmanned Aerial Vehicle and Operating Vehicle”

et al. 2021

View full text Add to dashboard Cite

In order to overcome the short battery life and poor long-distance maneuverability of Unmanned Aerial Vehicle (UAV) in power inspection operations, some provincial and municipal power companies promote a new mode of "UAV and operating vehicle (OV)" collaborative power inspection. This paper investigates into the actual problems in the cooperative inspection operations of the OV and multi-UAVs, and proposes a model of task allocation for the cooperative inspections of the OV and multi-UAVs, which includes four sub-problems: the division of a single operation circle, the location of parking spots, multi-UAVs task allocation, and the path planning of OV. The proposed model is solved by using improved K-means algorithm and genetic algorithm, and case analysis is carried out. The calculation results show that the model of task allocation for cooperative inspections proposed in this paper is practical and feasible, which can provide theoretical guidance for actual power inspections.

show abstract

A vehicle-UAV operation scheme for instant delivery

Cited by 50 publications

References 22 publications

Optimization of Rider Scheduling for a Food Delivery Service in O2O Business

Optimization of Rider Scheduling for a Food Delivery Service in O2O Business

Vehicle-Assisted UAV Delivery Scheme Considering Energy Consumption for Instant Delivery

The Collaborative Power Inspection Task Allocation Method of “Unmanned Aerial Vehicle and Operating Vehicle”

Contact Info

Product

Resources

About