Abstract
This paper addresses the problem of multi-objective coalition formation for task allocation. In disaster rescue, due to the dynamics of environments, heterogeneity and complexity of tasks as well as limited available agents, it is hard for the single-objective and single (task)-to-single (agent) task allocation approaches to handle task allocation in such circumstances. To this end, two multi-objective coalition formation for task allocation models are proposed for disaster rescues in this paper. First, through coalition formation, the proposed models enable agents to cooperatively perform complex tasks that cannot be completed by single agent. In addition, through adjusting the weights of multiple task allocation objectives, the proposed models can employ the linear programming to generate more adaptive task allocation plans, which can satisfy different task allocation requirements in disaster rescue. Finally, through employing the multi-stage task allocation mechanism of the dynamic programming, the proposed models can handle the dynamics of tasks and agents in disaster environments. Experimental results indicate that the proposed models have good performance on coalition formation for task allocation in disaster environments, which can generate suitable task allocation plans according to various objectives of task allocation.
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The work is supported by the National Natural Science Foundation of China (Grants No. 61402449, 91546111, 91646201, 61703013), and the Key Project of Beijing Municipal Education Commission (Grants No. KZ201610005009).
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Xing Su received his BSc in software engineering from Beijing University of Technology, China in 2007. He received his MSc and PhD in computer science from University of Wollongong, Australia in 2012 and 2015, respectively. From 2016, he works a lecturer in the Faculty of Information at the Beijing University of Technology in Beijing, China. His research interests include distributed artificial intelligence, multi-agent systems, disaster management and service-oriented computing.
Yuechen Wang received her BSc in computer science and technology from Hebei Normal University, China in 2016. From 2016, Yuechen studys as a postgraduate in College of Computer Science and Technology in Beijing University of Technology, China. Her research interests include multi-agent systems, disaster management, computer vision and affective computing.
Xibin Jia, born in 1969, received Ph.D. degree in computer science and technology from Beijing University of Technology in 2007, M.S. degree in intelligent instrument from North China Institute of Technology in 1996 and B.S. degree in wireless technology from Chongqing University in 1991. She is a Professor in the Faculty of Information at the Beijing University of Technology in Beijing, China. Her areas of interest include visual information cognition, multi-source information fusion and intelligent artification.
Limin Guo is a lecturer at the Beijing University of Technology. Her research interests include database research and implementation, spatial-temporal data mining, etc. She received her bachelor’s degree from Huazhong University of Science and Technology in 2005 and PhD degree in the Institute of Software, Chinese Academy of Sciences in 2012.
Zhiming Ding is a professor at the Beijing University of Technology, China. His main research interests include database systems, mobile & spatialtemporal data management, Intelligent Transportation Systems, sensor data management, and information retrieval. He received his bachelor’s degree, masters degree, and Ph.D. degree from Wuhan University (1989), Beijing University of Technology (1996), and Institute of Computing Technology, Chinese Academy of Sciences (2002), respectively. Before joining Beijing University of Technology in August 2014, he worked with the Institute of Scientific & Technical Information, Ministry of Communications of China (1989–1993), SINOCHEM (1996–1999), FernUniversitt in Hagen, Germany (2002–2004), and Institute of Software, Chinese Academy of Sciences (2004–2014). He owns 5 invention patents, and has published 3 books and about 110 papers in academic journals and conferences.
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Su, X., Wang, Y., Jia, X. et al. Two Innovative Coalition Formation Models for Dynamic Task Allocation in Disaster Rescues. J. Syst. Sci. Syst. Eng. 27, 215–230 (2018). https://doi.org/10.1007/s11518-018-5365-9
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DOI: https://doi.org/10.1007/s11518-018-5365-9