• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.167-178
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• 2019

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.243-249
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• 2018

This study is to verify the accommodation attitudes and intention of use of the end-users to use the drone distribution delivery service that is to be introduced in Korea. For a research purpose, the research model and hypothesis in this study have been set based on by using the SPSS 22.0. Upon these, the extended technology acceptance model has been used to verify the correlation service of new technology, and the result has shown that the user of drone distribution delivery service has a causal relationship with individual innovation and that the accommodation behavior and intention of use have a causal relationship with economic efficiency and convenience. However, there was no causal relation from a perceived risk. Hence, based on the results of study about accommodation behaviors and intention of use of the end users of drone distribution delivery service, the marketing implications have been provided for commercialization of drone delivery service.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.1-9
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• 2020

Global e-commerce and delivery companies are actively pursuing last-mile delivery service using drones, and various delivery schedule planning studies have been conducted. In this study, separate individual route networks were constructed to reflect drone route constraints such as prohibited airspace and truck route constraints such as rivers, which previous studies did not incorporate. The A* algorithm was used to calculate the shortest path distance matrix between the starting point and destinations. In addition, we proposed an optimal delivery schedule plan using genetic algorithms and applied it to compare the efficiency with that of vehicle-only delivery.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.106-116
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• 2021

This paper considers a joint problem for blood inventory planning at hospitals and blood delivery planning from blood centers to hospitals, in order to alleviate the blood service imbalance between big and small hospitals being occurred in practice. The joint problem is to determine delivery timing, delivery quantity, delivery means such as medical drones and legacy blood vehicles, and inventory level to minimize inventory and delivery costs while satisfying hospitals' blood demand over a planning horizon. This problem is formulated as a mixed integer programming model by considering practical constraints such as blood lifespan and drone specification. To solve the problem, this paper employs a Lagrangian relaxation technique and suggests a time efficient Lagrangian heuristic algorithm. The performance of the suggested heuristic is evaluated by conducting computational experiments on randomly-generated problem instances, which are generated by mimicking the real data of Korean Red Cross in Seoul and other reliable sources. The results of computational experiments show that the suggested heuristic obtains near-optimal solutions in a shorter amount of time. In addition, we discuss the effect of changes in the length of blood lifespan, the number of planning periods, the number of hospitals, and drone specifications on the performance of the suggested Lagrangian heuristic.

• Advances in aircraft and spacecraft science
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• v.10 no.6
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• pp.495-519
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• 2023

The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.

• Annual Conference of KIPS
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• 2016.04a
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• pp.168-170
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• 2016

Drone package delivery routing problem is realistic problem used to find efficient route of drone package delivery service. In this paper, we present an approach for solving drone routing problem for package delivery service using two different heuristics algorithms, genetic and nearest neighbor. We implement and analyze both heuristics algorithms for solving the problem efficiently with respect to cost and time. The respective experimental results show that for the range of customers 10 to 50 nearest neighbor and genetic algorithms can reduce the tour length on average by 34% and 40% respectively comparing to FIFO algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.204-209
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• 2016

In this paper, an unmanned delivery service using drone was proposed and verified the feasibility. The multicopter has GPS for autopilot and a camera for remote control by human operator. The gripper for manipulation of delivery object was designed and evaluated. The multicopter flies to a given position automatically based on GPS, and approaches to the prepared delivery desk by remote control of human operator using the received image from the multicopter. GPS sensor verification and experimental PID tuning were performed to ensure the flight stability. The flight tests were carried out to verify the feasibility of delivery service.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.915-920
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• 2015

Recently, many companies try to offer various services using drones. Especially, the drone delivery system is a good example. However, the drone delivery service has some problems since the heavy parcels flies over the people walking down streets, so many things must be considered such as dropping mails by collision of drones. To resolve the problem, in this paper, a inter-drone network communication will be used to design the topology and to simulate in the Opnet simulator for the performance evaluation. Additionally, the topology with random mobility of trajectory of drones is also designed and simulated for the result.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.141-150
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• 2023

Currently, various companies are actively participating in research and development of drone delivery services. Existing studies do not comprehensively provide integrated functions for future drone delivery services such as mission automation, customer verification, and overcoming performance limitations, which can lead to high manpower demand, reduced user service trust, and potentially overloading low-end devices. Therefore, this study proposes a drone mission automation system (DMAS) using EdgeCPS technology to provide the three aforementioned functions in an integrated manner. Real-world experiments were conducted to evaluate the proposed system, demonstrating that the DMAS components operate according to the specified roles in the delivery scenario. In addition, the system achieved user verification with a similarity of more than 90% in the process of receiving the product, and verified a faster inference speed and a lower resource share than the existing method.

• Advances in aircraft and spacecraft science
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• v.10 no.5
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• pp.393-418
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• 2023

Drones are increasingly used in logistics delivery due to their low cost, high-speed and straight-line flight. Considering the small cargo capacity, limited endurance and other factors, this paper optimized the pickup and delivery vehicle routing problem with time windows in the mode of "truck+drone". A mixed integer programming model with the objective of minimizing transportation cost was proposed and an improved adaptive large neighborhood search algorithm is designed to solve the problem. In this algorithm, the performance of the algorithm is improved by designing various efficient destroy operators and repair operators based on the characteristics of the model and introducing a simulated annealing strategy to avoid falling into local optimum solutions. The effectiveness of the model and the algorithm is verified through the numerical experiments, and the impact of the "truck+drone" on the route cost is analyzed, the result of this study provides a decision basis for the route planning of "truck+drone" mode delivery.