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Drones
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Advanced Operations Research of Unmanned Aerial Vehicle
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Advanced Operations Research of Unmanned Aerial Vehicle

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Communications".

Deadline for manuscript submissions: closed (14 August 2023) | Viewed by 4879

Special Issue Editors

Dr. Jianmai Shi

E-Mail Website
Guest Editor
Science and Technology on Information System Engineering Laboratory, National University of Defense Technology, Changsha 410073, China
Interests: battery electric vehicles; charging station; Local Search; location problem
Dr. Xinwei Wang

E-Mail Website
Guest Editor
Department of Transport & Planning, Delft University of Technology, Delft, The Netherlands
Interests: decision support systems; operational scheduling and optimisation for engineering applications
Prof. Dr. Guohua Wu

E-Mail Website
Guest Editor
School of Automation, Central South University, Changsha 410083, China
Interests: planning and scheduling; swarm intelligence; evolutionary computation; intelligent transportation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs), commonly known as drones, have been widely applied in various fields, including logistics, agriculture, patrolling, monitoring of traffic and infrastructure, and wireless networks. Compared to traditional vehicles, UAVs have many advantages in practical applications, such as low cost, high agility, less emissions, being contactless and having no risk of casualties. Thus, UAVs have a growing role in both civil and military operations, and their applications motivate a series of new operations research (OR) problems. This Special Issue aims to collect the recent advances in this broad topic, including the modeling and optimization methods. In typical operations research on UAVs, they are formulated as optimization problems, including objective functions, decision variables and the set of feasible solutions. Different types of OR problems need to be investigated under different application scenarios of UAVs. They might include drone route planning problems in logistic, path planning problems in area coverage, location routing problems with base stations, or drone deployment problems in communication relay. UAVs can also be employed with traditional vehicles, e.g., truck–drone cooperated delivery, which motivates more complex OR problems. Many OR problems for UAVs, such as routing, scheduling and deployment, are NP-hard and difficult to solve, and thus intelligent algorithms usually have to be designed for solving these problems. In this Special Issue, original research articles and reviews are welcome. Potential topics may include, but are not limited to, the following: routing problems for drones or cooperated drones and other vehicles, e.g., truck and drone cooperated delivery; deployment optimization for drones in communication and networking; multi-drone scheduling problem; path planning problem for drones in complex environment; OR applications of drones considering policies and regulations, such as maximum flight altitude, maximum payload and no-fly zones; energy evaluation and management for drone applications; dynamic systems with drones, such as dynamic customer requests or on-demand delivery; behavior of drone-aided systems under uncertainty; intelligent algorithms for solving OR problem with drones.

Dr. Jianmai Shi
Dr. Xinwei Wang
Prof. Dr. Guohua Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • unmanned aerial vehicle
  • operations research
  • intelligent optimization

Published Papers (3 papers)

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Research

25 pages, 5804 KiB  
Article
Joint Deployment and Coverage Path Planning for Capsule Airports with Multiple Drones
by Weichang Sun, Zhihao Luo, Kuihua Huang and Jianmai Shi
Drones 2023, 7(7), 457; https://doi.org/10.3390/drones7070457 - 9 Jul 2023
Viewed by 1389
Abstract
Due to the advantages of low cost and high flexibility, drones have been applied to urban surveillance, vegetation monitoring, and other fields with the need for coverage of regions. To expand UAVs’ coverage, we designed the Capsule Airport (CA) to recharge and restore [...] Read more.
Due to the advantages of low cost and high flexibility, drones have been applied to urban surveillance, vegetation monitoring, and other fields with the need for coverage of regions. To expand UAVs’ coverage, we designed the Capsule Airport (CA) to recharge and restore drones and provide take-off and landing services. Meanwhile, the combination of drones’ coverage path planning (CPP) and the deployment of CAs is a crucial problem with few relevant studies. We propose a solution approach to the CPP problem based on selecting scanning patterns and trapezoidal decomposition. In addition, we construct a 0–1 integer programming model to minimize the cost of the distance between CAs and the scanning missions. Specifically, a solution approach based on greedy and clustering heuristics is designed to solve this problem. Furthermore, we then develop a local-search-based algorithm with the operators of CA location exchange and drone scanning mission exchange to further optimize the solution. Random instances at different sizes are used to validate the performance of proposed algorithms, through which the sensitivity analysis is conducted with some factors. Finally, a case study based on the Maolichong forest park in Changsha, China, is presented to illustrate the application of the proposed method. Full article
(This article belongs to the Special Issue Advanced Operations Research of Unmanned Aerial Vehicle)
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20 pages, 2703 KiB  
Article
Multi-Perspective Investigations Based Design Framework of an Electric Propulsion System for Small Electric Unmanned Aerial Vehicles
by Surenther Kulanthipiyan, Parvathy Rajendran and Vijayanandh Raja
Drones 2023, 7(3), 184; https://doi.org/10.3390/drones7030184 - 7 Mar 2023
Cited by 2 | Viewed by 1482
Abstract
Numerous attempts have been made to extend the endurance of small unmanned aerial vehicles (UAVs) by improving their propulsion system. However, due to their non-linear setup, no study has been conducted on small electric UAVs’ architecture framework. This study established a novel propulsion [...] Read more.
Numerous attempts have been made to extend the endurance of small unmanned aerial vehicles (UAVs) by improving their propulsion system. However, due to their non-linear setup, no study has been conducted on small electric UAVs’ architecture framework. This study established a novel propulsion system framework model by analyzing 42 existing UAV electric propulsion systems. The proposed framework-based complicated model includes a new torque factor used to determine the operating current and voltage of the system. This innovative approach improved the model accuracy for the non-linear behavioral nature-based electrical and mechanical systems. The findings include a reduced electrical current usage of up to 84% and an average reduction of 26%. In addition, the investigation also found that the durability of the propulsion systems improved by 53% on average. Similarly, improvements in the trust-to-weight ratio were also established. As a result, a method of propeller matching is presented to facilitate the broad implementation of the proposed framework. The performance of the existing propulsion system was enhanced by using the proposed framework. Full article
(This article belongs to the Special Issue Advanced Operations Research of Unmanned Aerial Vehicle)
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18 pages, 2141 KiB  
Article
Scheduling Drones for Ship Emission Detection from Multiple Stations
by Zhi-Hua Hu, Tian-Ci Liu and Xi-Dan Tian
Drones 2023, 7(3), 158; https://doi.org/10.3390/drones7030158 - 24 Feb 2023
Viewed by 1357
Abstract
Various port cities and authorities have established emission control areas (ECAs) to constrain ships’ fuel usage in a specified offshore geographical range. However, these ECA policies involve high costs and have low monitoring and regulation enforcement efficiencies. In this study, a meeting model [...] Read more.
Various port cities and authorities have established emission control areas (ECAs) to constrain ships’ fuel usage in a specified offshore geographical range. However, these ECA policies involve high costs and have low monitoring and regulation enforcement efficiencies. In this study, a meeting model was used to investigate the drone-scheduling problem by considering the simultaneous movements of drones and ships. Set-covering integer linear programs were developed to formulate the assignments of drones to ships, and a model and solution algorithm were devised to determine the moving times and meeting positions for particular drones and ships. The proposed models and algorithms were employed and verified in experiments. The flying times for the datasets with three drone base stations were shorter than those with two. More drones resulted in shorter flying distances. The use of the meeting model enabled the acquirement of shorter flying times and distances than when it was not used. The datasets with more ships had longer flying times and distances, with almost linear relationships. The sensitivity of the effect of varying 5% of the ships’ speeds on the flying time metrics was less than 1%, affecting the flying distance by about 4–5%. Accelerating the drones was more effective towards optimizing the drones’ flying distances than times. Numerical studies showed that the consideration of simultaneous movements in the model allowed for a reduction in the drones’ flying distances and increased efficiency. Based on the modeling and experimental studies, managerial implications and possible extensions are discussed. Full article
(This article belongs to the Special Issue Advanced Operations Research of Unmanned Aerial Vehicle)
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