The household waste collection points location problem with nearest-allocation and waste classification in rural...

Household waste management in rural areas has become a major challenge in China. A reasonable setup of collection points can improve the efficiency of waste management. Considering waste classification and the differences in the disposal habits of residents, the coverage radius of bins is defined on the basis of waste type. Each type of waste at every demand point must be assigned to the nearest facility located within the corresponding coverage radius. In accordance with the "Not In My Back Yard" effect, the minimum acceptable distance is also considered in the model. Two integer programming models are proposed, one for deterministic demand and the other for variable food waste demand. The locations of collection points and the number of bins for each type of waste at each collection point should be determined. The goal is to minimize total costs, comprising setup costs, bin-related variable costs, and penalties from food waste demand fluctuations. To solve the models, heuristic algorithms based on Lagrangian relaxation are developed. A case study in rural Xi'an demonstrates the feasibility and effectiveness of the proposed models and algorithm. On the basis of the results, heterogeneous coverage radii can reduce the total cost and increase the average utilization rate of waste bins, with a limited increase in walking distance. Introducing penalty costs for food waste demand fluctuations minimizes penalties without increasing facility setup costs, achieved by adding a small number of food waste bins and adjusting facility locations and bin allocations, while maintaining resident walking distances.