Urban Solid Waste Storage and Transportation Management Model Based on Improved Genetic Algorithm and Circular Economy

With the acceleration of urbanization, the storage and management of urban solid waste have become increasingly prominent, causing serious pollution and resource waste to the environment. However, the existing solid waste management models often face limitations such as low efficiency, high cost and suitability for optimization. There is an urgent need to seek an efficient and sustainable management solution. The research aims to improve the storage and transportation efficiency of urban solid waste by constructing a management model for the storage and transportation of urban solid waste based on the improved genetic algorithm and large neighborhood search, maximize the utilization of waste recycling economy, and reduce treatment costs and environmental pollution. This method represents the solid waste transportation routes as chromosomes through character encoding and designs a multi-objective fitness function to evaluate the quality of the solutions. Secondly, new solutions are generated by using selection, crossover and mutation operations. Finally, the destruction and repair mechanism of large neighborhood search is introduced to locally optimize the current solution to improve the search efficiency and the quality of the solution. The experimental results show that the research method has excellent performance in terms of cost control and time efficiency. This new model can not only optimize the management efficiency of solid waste, but also provide scientific decision support for urban management departments, promote the practical application of circular economy, and has practical value and broad promotion potential.