Abstract
The sharing economy plays an important role in economic development, and matching is the core point in the sharing economy. However, the large-scale sharing results in low efficiencies and weak matching. To address the problem, we design a two-stage consensus reaching process for resource sharing in the platform. Firstly, considering the time-consuming process of generating satisfaction, we design a new method to generate satisfaction based on large-scale mixed historical data. The cloud model is used to unify the mixed uncertain information. Then, we design a two-stage consensus reaching process to realize stable matching. For the first stage, we maximize the total consensus of the suppliers’ and demanders’ group. For the second stage, to realize stable sharing, we satisfy the individuals’ requirement of consensus. The platform’s strategies, such as discount and scheduling, are used to adjust their consensus. Finally, considering the two-stage consensus reaching process hierarchy, we establish bi-level programming to embody the features. An improved algorithm is designed to deal with bi-level programming. Also, an industrial internet platform is used as an example to verify the method and algorithm.
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Funding
The study is supported by the National Natural Science Foundation of China (71502073, 72071106) and the Postgraduate Research and Practice Innovation Program of Jiangsu Province (NO.KYCX19_0146).
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HT contributed to conceptualization, formal analysis, and investigation, methodology, writing—original draft. JZ contributed to conceptualization, methodology, supervision, resources, writing—review and editing. XT contributed to the formal analysis and investigation, writing—review and editing.
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Tong, H., Zhu, J. & Tan, X. Two-stage consensus reaching process for matching based on the cloud model in large-scale sharing platform: a case study in the industrial internet platform. Soft Comput 26, 3469–3488 (2022). https://doi.org/10.1007/s00500-022-06732-6
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DOI: https://doi.org/10.1007/s00500-022-06732-6