Optimization of Urban Garbage Classification Transportation Path Based on NSGA-II algorithm

As China's urbanization accelerates, the volume of urban waste is increasing, making waste management a growing concern. In recent years, the Chinese government has been actively promoting waste sorting policies to enhance resource recovery rates, reduce environmental pollution, and promote sustainable development. The comprehensive implementation of these policies has led to a shift in the waste transportation system from a traditional mixed collection model to a specialized classified transportation model. This transformation not only improves the efficiency and quality of waste processing but also imposes higher demands on the planning and management of waste transportation. This paper focuses on optimizing the transportation routes for urban waste sorting, aiming to reduce transportation costs and improve efficiency by optimizing these routes. To achieve this, a multi-objective optimization model based on the Non-Dominating Sorting Genetic Algorithm (NSGA-II) is proposed, which takes into account the transportation needs of different types of waste, vehicle capacity constraints, and time window limitations. Finally, through practical case studies, it is demonstrated that the optimized transportation routes have significantly reduced total transportation costs and improved transportation times, providing a scientific basis for the management of urban waste sorting transportation.