Research on innovation of public service supply mechanism from the perspective of social cooperative governance based on improved genetic algorithms using fuzzy TOPSIS
Issue title: Ethical Computational Intelligence for Cyber Market
Guest editors: Oscar Sanjuán Martínez, Giuseppe Fenza and Ruben Gonzalez Crespo
Affiliations: School of Information Engineering, Nanjing XiaoZhuang University, Nanjing, Jiangsu, China
Correspondence:
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Corresponding author. Wang Zheng, School of Information Engineering, Nanjing XiaoZhuang University, Nanjing 211171, Jiangsu, China. E-mail: wangzheng@njxzc.edu.cn.
Abstract: With the deepening of reform and opening up, the social management function of county government is becoming more and more important. As one of the symbols of the maturity of modern country, public service function is not only a test of the comprehensive ability of the country, but also a profound practice of serving the people. Aiming at the problem that traditional genetic algorithm is easy to fall into local optimal solution and its performance is unstable, an adaptive genetic algorithm (CEAGA) based on co-evolution is proposed. And then combined with some of the constraints inherent in the battlefield situation, a comprehensive evaluation model was established. The analysis on social cooperative governance is carried based on the fuzzy TOPSIS which is utilised for making multi criteria decision making situations. Research shows that the innovation of the public service supply mechanism must respect the reality of China’s political ecology, ensure the government’s dominant position in the governance of public affairs, and at the same time correctly respond to the development of social forces. The theory of collaborative governance also provides a new research perspective for the innovation and development of public service mechanisms.
Keywords: Improved genetic algorithm, social collaborative governance, public
service, supply mechanism innovation, fuzzy TOPSIS
