Abstract
With the development of Big Data, Industry 4.0, and other technologies, the concept of smart city has become a new goal, new concept, and new practice of many urban developments. It provides a method to solve the problem that public management cannot optimize resources in China’s urban development and puts forward a supporting scheme more in line with the optimization of public management resources. Effective use of relevant supporting schemes can improve urban public management capacity, optimize resources, and promote the city to embark on the road of scientific development. This paper starts with the multiobjective optimization algorithm to optimize the matching of public resources and realize the effective utilization of public management resources. Using particle swarm optimization algorithm, the optimal allocation management of 8 kinds of resources in this paper is carried out, and the optimization analysis is carried out from the performance indexes, such as resource allocation time and configuration complexity. Finally, the weights of the eight resources in importance, complexity, and resource demand are 0.4, 0.4, and 0.2, respectively. The proposed method realizes the classification of resources and the optimal matching of resources.
Highlights
Driven by the tide of urban informationization and the rise of data science, smart cities have become a new concept and practice of future urban development on a global scale
Arbolino et al [5] proposed a new method for selecting public administrationfunded projects, which is suitable for the planning of sustainable tourism activities and can maximize the allocation efficiency
Herguner [6] verified exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) in the form of questionnaires and proposed a CC evaluation model. e model consists of five key attributes, which involve all aspects of cultural ability
Summary
Driven by the tide of urban informationization and the rise of data science, smart cities have become a new concept and practice of future urban development on a global scale. Researchers put forward that the innovation of public sector involves computerization, continuous optimization, adapting to the changes, and making its image more suitable for the needs of smart city construction. Arbolino et al [5] proposed a new method for selecting public administrationfunded projects, which is suitable for the planning of sustainable tourism activities and can maximize the allocation efficiency. Complexity resources based on genetic algorithm and cloud computing, which takes the running time and cost of public resources as the optimization objectives, and put forward the adaptive function of population constraint. E objectives refer to the target requirements such as time, task coupling, and resource demand By optimizing these goals, we can optimize the resources of smart cities and maximize the benefits
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