Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
In the context of rapid urbanization and the substantial increase in logistics demand, the deployment of Unmanned Aerial Vehicle (UAV) delivery systems has emerged as a pivotal technology for augmenting delivery efficiency and enhancing customer satisfaction. This study tackles the intricate challenge of task allocation among multiple logistics UAVs within urban delivery scenarios, striving to simultaneously minimize transportation costs and maximize customer satisfaction by optimizing the task allocation mechanism. To-wards this objective, we have conceptualized a multi-logistics UAV task allocation model and engineered an avant-garde Improved Genetic Algorithm (IGA) to address this model effectively. The algorithm amalgamates a multi-round roulette selection strategy with a tournament selection mechanism, markedly augmenting the likelihood of selecting superior individuals. Through the amalgamation of sequential and two-point crossover techniques, alongside refined mutation probabilities adjustments, it considerably bolsters search accuracy and expedites the algorithm's convergence rate. Furthermore, the algorithm employs a variegated suite of crossover and mutation strategies to foster population diversity and ensure the preservation of elite individuals, concurrently facilitating the advancement of less fit individuals. Empirical simulation outcomes attest that the enhanced genetic algorithm secures approximately a 50% enhancement in the average fitness function value, adeptly engineering task allocation solutions that are cost-effective and yield higher customer satisfaction, thereby manifesting a pronounced competitive edge over conventional genetic algorithms. This inquiry not only unveils novel avenues for the refinement of UAV logistics delivery systems but also furnishes substantial theoretical underpinnings and pragmatic insights for the intellectualization of future urban community logistics distribution networks.
In the context of rapid urbanization and the substantial increase in logistics demand, the deployment of Unmanned Aerial Vehicle (UAV) delivery systems has emerged as a pivotal technology for augmenting delivery efficiency and enhancing customer satisfaction. This study tackles the intricate challenge of task allocation among multiple logistics UAVs within urban delivery scenarios, striving to simultaneously minimize transportation costs and maximize customer satisfaction by optimizing the task allocation mechanism. To-wards this objective, we have conceptualized a multi-logistics UAV task allocation model and engineered an avant-garde Improved Genetic Algorithm (IGA) to address this model effectively. The algorithm amalgamates a multi-round roulette selection strategy with a tournament selection mechanism, markedly augmenting the likelihood of selecting superior individuals. Through the amalgamation of sequential and two-point crossover techniques, alongside refined mutation probabilities adjustments, it considerably bolsters search accuracy and expedites the algorithm's convergence rate. Furthermore, the algorithm employs a variegated suite of crossover and mutation strategies to foster population diversity and ensure the preservation of elite individuals, concurrently facilitating the advancement of less fit individuals. Empirical simulation outcomes attest that the enhanced genetic algorithm secures approximately a 50% enhancement in the average fitness function value, adeptly engineering task allocation solutions that are cost-effective and yield higher customer satisfaction, thereby manifesting a pronounced competitive edge over conventional genetic algorithms. This inquiry not only unveils novel avenues for the refinement of UAV logistics delivery systems but also furnishes substantial theoretical underpinnings and pragmatic insights for the intellectualization of future urban community logistics distribution networks.
A robust control method based on the leader-follower control configuration is proposed for the formation tracking control issue of a multi-unmanned aerial vehicle (multi-UAV) system under the simultaneous presence of time-delay and external disturbances. First, based on consensus control theory, a distributed formation tracking control protocol is designed to account for the presence of time-delay and external disturbances. Then, by substituting the control protocol into the system model and employing variable substitutions, the formation tracking control problem of the multi-UAV system is transformed into the issue of asymptotic stability for a time-delay system. Furthermore, by constructing a set of linear matrix inequalities, the maximum allowable upper bound for the time delay that guarantees the stability of the time-delay system is calculated. Additionally, using Lyapunov stability theory, the correctness of the method for calculating asymptotic stability and the time-delay upper bound is demonstrated. Finally, numerical simulation experiments are conducted with a multi-UAV system consisting of five drones. The results show that the designed control protocol can achieve rapid and smooth formation tracking control under the simultaneous presence of time-delay and external disturbances.
Kültürel miras, geçmişin izlerini günümüze taşıyan, toplumların kimliklerini belirleyen önemli bir unsurdur. Ancak, bu tarihi zenginliklerin zaman içinde kaybolma veya zarar görme riski vardır. Bu nedenle, kültürel mirasın korunması ve gelecek nesillere aktarılması büyük bir öneme sahiptir. Geleneksel koruma yöntemlerinin yanı sıra, günümüzde dijital teknolojilerin kültürel mirası koruma ve erişim açısından yeni fırsatlar sunduğu bir döneme tanık olmaktayız. Bu makalede, kültürel mirasın dijital arşivlenmesi konusunda bir örnek çalışma sunulmaktadır: Emirci Saltuk Türbesi. Türbe, tarihi ve kültürel öneme sahip olmasıyla birlikte, zaman içinde çeşitli etkilere maruz kalarak bozulma riski altındadır. Bu durumu göz önünde bulundurarak, geleneksel belgeleme yöntemlerinin ötesine geçerek dijital teknolojilerin gücünü kullanmak, kültürel mirasın kayıt altına alınması ve gelecek nesillerle paylaşılması açısından kritik bir adımdır. Emirci Saltuk Türbesi'nin fotogrametrik yöntemlerle dijital olarak modellenmesi ve bu dijital arşivin, tarihi ve kültürel olarak sürdürülebilir kılınması, korunması ve belgelenmesi gerekmektedir. Fotogrametri, İnsansız Hava Araçları (İHA) ve diğer dijital araçların entegrasyonu, kültürel mirasın korunması ve erişim sağlanmasında etkili bir yol sunmaktadır. Emirci Saltuk Türbesi örneği üzerinden yürütülen dijital arşivleme çalışmanda metodoloji, elde edilen sonuçlar ve projenin kültürel mirasın dijitalleştirilmesine sağladığı katkılara değinilmiştir. Çalışmada nokta bulutu, ortofoto, sayısal yükseklik modeli ve 3 buyutlu model üretilmiştir. Arşivleme çalışmasında yapının 3 boyutlu modeli 1.29 cm konum doğruluğunda üretilmiştir.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.