Application of Improved Genetic Optimization Algorithm in Intelligent Management of Economy

As an important part of urban development, night economy has become a new engine of economic growth with the change of times and the improvement of consumption demand. However, the night economic management is faced with many complex problems such as rational allocation of resources, safety management, marketing and so on. The purpose of this study is to explore the application of genetic optimization algorithm in intelligent management of night economy. This paper first introduces the concept and importance of night economy, then explains the basic principle of genetic algorithm and its advantages in optimization problems. By analyzing the specific problems of night economy management, such as resource allocation and security management, these problems are formalized into optimization models that can be solved by genetic algorithm. In this paper, a practical case is selected to show the application process and effect of genetic optimization algorithm in night economy management. The key steps, parameter setting and optimization results of the algorithm are discussed. The practicability and effectiveness of the algorithm in night economy intelligent management are proved. At the same time, the possible challenges in the application process are discussed, and the improvement of the algorithm and the future research direction are put forward. The purpose of this study is to provide innovative and intelligent solutions for night economy management, to promote the sustainable development of night economy, and to provide reference and inspiration for other fields of intelligent management.