Research on innovation of public service supply mechanism from the perspective of social cooperative governance based on improved genetic algorithms using fuzzy TOPSIS

2021 ◽  
pp. 1-10
Author(s):  
Wang Zheng

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.

2013 ◽  
Vol 694-697 ◽  
pp. 2895-2900 ◽  
Author(s):  
Xiao Yang ◽  
Bo Jiang

Since the beginning of the twenty-first century, energy conservation has become the theme of the development of the world. China government set the emissions-reduction targets in various industries on the 12th Five-Year Plan. And the airlines were committed to reduce their carbon emissions. From an operational perspective, the airline model assignment problem is a key factor of the total carbon emissions on the entire route network. But the traditional aircraft assignment models approach did not account for this purpose to reduce carbon emissions. By constructing the multi-objective optimization models consider carbon emissions assignment model using a genetic algorithm, numerical example shows that the model is able to meet all aspects demand which include meeting route network capacity demand, minimizing operating costs and reducing total aircraft fleet carbon emissions.


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