Relevant bibliographies by topics / Auction-based task allocation

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Auction-based task allocation'

Author: Grafiati
Published: 14 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Auction-based task allocation"

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Baroudi, Uthman, Mohammad Alshaboti, Anis Koubaa, and Sahar Trigui. "Dynamic Multi-Objective Auction-Based (DYMO-Auction) Task Allocation." Applied Sciences 10, no. 9 (2020): 3264. http://dx.doi.org/10.3390/app10093264.

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In this paper, we address the problem of online dynamic multi-robot task allocation (MRTA) problem. In the existing literature, several works investigated this problem as a multi-objective optimization (MOO) problem and proposed different approaches to solve it including heuristic methods. Existing works attempted to find Pareto-optimal solutions to the MOO problem. However, to the best of authors’ knowledge, none of the existing works used the task quality as an objective to optimize. In this paper, we address this gap, and we propose a new method, distributed multi-objective task allocation
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Rub, Abd Ur, and Lu Xuanmin. "Multiple Task Assignment Algorithms for Unmanned Aerial Vehicles." Journal of Engineering Research and Reports 26, no. 7 (2024): 26–42. http://dx.doi.org/10.9734/jerr/2024/v26i71191.

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To fulfill the requirement of assigning task the auction algorithm is widely used. There are many classical auction algorithms those performances not up to the mark while dealing with multi-UAVs dynamic task assignment. SWARM UAVs are made up of a large number of small UAVs with limited mission resources that can operate in an autonomous, appropriate and universal manner. Based on the in-depth research of the traditional auction algorithm CAA, this paper proposes an iterative method that can improve the task allocation efficiency of multi-UAV, namely the two-stage auction algorithm. At the sam
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Lu, Ye, Rui Zhou, Xing Li, Zhiheng Liu, and Bin Di. "Heterogeneous multi-task allocation algorithm based on multi-round distributed auction." Journal of Applied Artificial Intelligence 1, no. 2 (2024): 101–13. http://dx.doi.org/10.59782/aai.v1i2.293.

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Aiming at the distributed decision-making needs of different combat tasks such as multi-machine collaborative detection, attack, and evaluation, a multi-round distributed auction algorithm for heterogeneous tasks with time constraints is established. The algorithm flexibly solves the distributed collaborative task allocation problem with complex constraints between drones with different capabilities. In the distributed task allocation framework, each drone can realize distributed asynchronous computing and asynchronous communication, and can ensure good solution efficiency and accuracy. The ta
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Zhang, Jiandong, Yuyang Chen, Qiming Yang, et al. "Dynamic Task Allocation of Multiple UAVs Based on Improved A-QCDPSO." Electronics 11, no. 7 (2022): 1028. http://dx.doi.org/10.3390/electronics11071028.

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With the rapid changes in the battlefield situation, the requirement of time for UAV groups to deal with complex tasks is getting higher, which puts forward higher requirements for the dynamic allocation of the UAV group. However, most of the existing methods focus on task pre-allocation, and the research on dynamic task allocation technology during task execution is not sufficient. Aiming at the high real-time requirement of the multi-UAV collaborative dynamic task allocation problem, this paper introduces the market auction mechanism to design a discrete particle swarm algorithm based on par
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Liang, Yajie, Kun Zhou, and Caicong Wu. "Dynamic Task Allocation Method for Heterogenous Multiagent System in Uncertain Scenarios of Agricultural Field Operation." Journal of Physics: Conference Series 2356, no. 1 (2022): 012049. http://dx.doi.org/10.1088/1742-6596/2356/1/012049.

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This study focuses on the problem of dynamic task allocation for a heterogeneous multiagent system (MAS) in uncertain scenarios and its application in agricultural field operation. Previous studies lacked robustness or efficiency for uncertain environments especially in agricultural field, such as agent removal, agent inclusion, changes of agent capabilities, and task changes. We present herein a novel concept of the potential field of capability influence (PFCI), and based on which, we can estimate potential overloaded tasks. This provides an opportunity to improve the allocation of the remai
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Fang, Baofu, Lu Chen, Hao Wang, Shuanglu Dai, and Qiubo Zhong. "Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor." Scientific World Journal 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/864180.

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Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots’ individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and te
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Braquet, Martin, and Efstathios Bakolas. "Greedy Decentralized Auction-based Task Allocation for Multi-Agent Systems." IFAC-PapersOnLine 54, no. 20 (2021): 675–80. http://dx.doi.org/10.1016/j.ifacol.2021.11.249.

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Zhenyu Wu, Minhua Xiao, Bo Jin, and Lin Feng. "Dynamic task allocation based on distance of superior probability auction." Journal of Convergence Information Technology 7, no. 2 (2012): 10–17. http://dx.doi.org/10.4156/jcit.vol7.issue2.2.

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He, Jianhua, Siqi Tao, Yang Deng, Libin Chen, and Zhiying Mou. "Research on Multi-Sensor Resource Dynamic Allocation Auction Algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, no. 2 (2019): 330–36. http://dx.doi.org/10.1051/jnwpu/20193720330.

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This paper designs a multi-sensor resource dynamic allocation method based on auction algorithm. Tasks are prioritized according to the needs of the engineering field. Task priority is used as the basis for multi-sensor resource allocation order, taking into account the target's threat value and information needs. The sensor and task pairing function is established and used to measure the sensor resource dynamic allocation, we also use Analytic Hierarchy Process to determine the weight of each performance parameter in the pairing function (such as detection probability, intercept probability,
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Fazal, Nayyer, Muhammad Tahir Khan, Shahzad Anwar, Javaid Iqbal, and Shahbaz Khan. "Task allocation in multi-robot system using resource sharing with dynamic threshold approach." PLOS ONE 17, no. 5 (2022): e0267982. http://dx.doi.org/10.1371/journal.pone.0267982.

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Task allocation is a fundamental requirement for multi-robot systems working in dynamic environments. An efficient task allocation algorithm allows the robots to adjust their behavior in response to environmental changes such as fault occurrences, or other robots’ actions to increase overall system performance. To address these challenges, this paper presents a Task Allocation technique based on a threshold level which is an accumulative value aggregated by a centralized unit using the Task-Robot ratio and the number of the available resource in the system. The threshold level serves as a refe
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Dissertations / Theses on the topic "Auction-based task allocation"

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Koung, Daravuth. "Cooperative navigation of a fleet of mobile robots." Electronic Thesis or Diss., Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0044.

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L’intérêt pour l’intégration des systèmes multi-robots (MRS) dans les applications du monde réel augmente de plus en plus, notamment pour l’exécution de tâches complexes. Pour les tâches de transport de charges, différentes stratégies de manutention de charges ont été proposées telles que : la poussée seule, la mise en cage et la préhension. Dans cette thèse, nous souhaitons utiliser une stratégie de manipulation simple : placer l’objet à transporter au sommet d’un groupe de robots mobiles. Ainsi, cela nécessite un contrôle de formation rigide. Nous proposons deux algorithmes de formation. L’a
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Book chapters on the topic "Auction-based task allocation"

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Pereira, Eliseu, João Reis, Gil Gonçalves, Luís Paulo Reis, and Ana Paula Rocha. "Dutch Auction Based Approach for Task/Resource Allocation." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79168-1_30.

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Tao, Xue-li, and Yan-bin Zheng. "Multi-agent Task Allocation Method Based on Auction." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14350-2_27.

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Shi, Jieke, Zhou Yang, and Junwu Zhu. "An Auction-Based Task Allocation Algorithm in Heterogeneous Multi-Robot System." In 2nd EAI International Conference on Robotic Sensor Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17763-8_14.

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Schneider, Eric, Elizabeth I. Sklar, Simon Parsons, and A. Tuna Özgelen. "Auction-Based Task Allocation for Multi-robot Teams in Dynamic Environments." In Towards Autonomous Robotic Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22416-9_29.

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Xiao, Junlei, Peng Li, and Lei Nie. "A Reliable Multi-task Allocation Based on Reverse Auction for Mobile Crowdsensing." In Wireless Algorithms, Systems, and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59016-1_44.

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Wei, Changyun, Koen V. Hindriks, and Catholijn M. Jonker. "Auction-Based Dynamic Task Allocation for Foraging with a Cooperative Robot Team." In Multi-Agent Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17130-2_11.

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Mo, Zijing, Tingting Zhang, Xuan Zhou, Chang Wang, and Lizhen Wu. "Multi-UAV Cooperative Task Allocation Based on Fish Swarm Auction Hybrid Algorithm." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2468-3_49.

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Bao, Kanghua, Shuang Yi, Hongjiang Zhang, and Pengsheng He. "Multi-unmanned Aerial Vehicle Cooperative Task Allocation Algorithm Based on Improved Distributed Cooperative Auction." In Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022). Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0479-2_141.

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Quinton, Félix, Christophe Grand, and Charles Lesire. "Improving the Connectivity of Multi-hop Communication Networks Through Auction-Based Multi-robot Task Allocation." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18192-4_28.

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Ramezani, Fahimeh, Brendan Sims, and Haris Aziz. "Auction-Based Allocation of Location-Specific Tasks." In Lecture Notes in Computer Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8391-9_20.

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Conference papers on the topic "Auction-based task allocation"

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Yunhui, Wu, Wan Kaifang, Wu Zhilin, Qiang Haozhi, and Gao Xiaoguang. "Research on manned/unmanned aircraft formation cooperative task allocation based on hierarchical hybrid auction algorithm." In 2024 International Conference on Cyber-Physical Social Intelligence (ICCSI). IEEE, 2024. https://doi.org/10.1109/iccsi62669.2024.10799444.

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Hossain, Md Sabbir, and Naoki Fukuta. "Toward Parallel Task Allocation in Multi-Robot Environment Based on Auction Mechanism with Deadlock Constrains." In 2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2024. http://dx.doi.org/10.1109/iiai-aai63651.2024.00142.

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Ji, Guanfeng, Zhuo Zhang, Guan Huang, et al. "Hybrid Algorithm Research Based on Improved Genetic Algorithm and Auction Algorithm for AUVs Task Allocation*." In 2024 International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE, 2024. http://dx.doi.org/10.1109/icarm62033.2024.10715788.

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Gurel, Ugur, Nihat Adar, and Osman Parlaktuna. "Priority-based task allocation in auction-based applications." In 2013 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA). IEEE, 2013. http://dx.doi.org/10.1109/inista.2013.6577654.

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Harman, Helen, and Elizabeth Sklar. "Auction-based Task Allocation Mechanisms for Managing Fruit Harvesting Tasks." In UKRAS21 Conference: Robotics at home. EPSRC UK-RAS Network, 2021. http://dx.doi.org/10.31256/dg2zp9q.

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Hoeing, Matthew, Prithviraj Dasgupta, Plamen Petrov, and Stephen O'Hara. "Auction-based multi-robot task allocation in COMSTAR." In the 6th international joint conference. ACM Press, 2007. http://dx.doi.org/10.1145/1329125.1329462.

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Wen, Xiao, and Zhen-Gang Zhao. "Multi-Robot Task Allocation Based on Combinatorial Auction." In 2021 9th International Conference on Control, Mechatronics and Automation (ICCMA). IEEE, 2021. http://dx.doi.org/10.1109/iccma54375.2021.9646189.

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Zhang, Ziying, Jie Wang, Dong Xu, and Yulong Meng. "Task Allocation of Multi-AUVs Based on Innovative Auction Algorithm." In 2017 10th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2017. http://dx.doi.org/10.1109/iscid.2017.231.

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Wu, Shiguang, Xiaojie Liu, Xingwei Wang, Xiaolin Zhou, and Mingyang Sun. "Multi-robot Dynamic Task Allocation Based on Improved Auction Algorithm." In 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE). IEEE, 2021. http://dx.doi.org/10.1109/cacre52464.2021.9501305.

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Mingqiu, Ren, Liu Junkai, and Shang Ben. "Adaptive Task Scheduling and Resources Allocation Based on Auction Algorithm." In 2021 13th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2021. http://dx.doi.org/10.1109/ihmsc52134.2021.00052.

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