Research on Path Optimization of Urban Garbage Classification and Transportation Based on CVRP Model

Abstract

With the acceleration of urbanization in China, the management of urban household waste is facing severe challenges. Optimizing and scheduling the path of garbage classification and transportation has become the key to improving efficiency and reducing costs. This article is based on the Vehicle Routing Problem (CVRP) model and combines multi-objective optimization methods to study complex scenarios involving single vehicles, multi vehicle collaboration, and intermediate stations. This article establishes a CVRP model with capacity constraints and uses greedy algorithm to generate paths, achieving the minimization of total driving distance. Through the verification of 30 collection points, the total driving distance was optimized to 1332.9 kilometers, and the time complexity and limitations of the algorithm were analyzed. The feasibility of introducing dynamic road network data to improve path planning was proposed. Then, the extended model is used for multi vehicle collaborative scheduling, taking into account the differences in load capacity, volume, and cost among the four types of garbage. Design a categorized path optimization algorithm to achieve the optimal solution for a total transportation cost of 1402.4 yuan, and explore the impact of time constraints on task splitting to verify the flexibility and robustness of the model.