Industrial Economy and Regional Growth Strategy Based on Particle Swarm Optimization Algorithm

With the rapid growth of the global economy, it has become an inevitable trend for Chinese enterprises to transform and upgrade their industries. This paper starts with the research status at home and abroad, and analyzes the problems existing in the current industrial growth of China in combination with relevant literature and cases in the industry. Then, through the research of particle swarm optimization (PSO) algorithm, the growth trajectory of major cities in China and the regional competition status of each region are summarized. Finally, the PSO algorithm is applied to the optimization solution model of the location of industries in various provinces and cities in China based on the regional economic and social growth strategy, and the final results are obtained. The results show that the coordinated growth coefficient and comprehensive growth level are about 5 and 7 in this model, The level of coordinated growth is shown in 5 test results. Therefore, the industrial economy and regional growth strategy model based on PSO algorithm meets the needs of users.