This study focuses on improving the efficiency of a voluntary plastic recycling project. The waste collection operation involves gathering used plastic bags and films from households and businesses and delivering them to a recycling facility. As the project operates on a non-profit basis, managing operational costs is essential. Transportation is one of the primary cost components, so this study introduces a three-step method to optimize collection routes and enhance resource efficiency.

In the first step, nearby collection points are grouped together using K-means clustering. This simplifies the routing problem by reducing complexity and ensuring that trips are localized within smaller geographic zones. In the second step, the method identifies which collection points within each cluster should be visited on a given day. The goal is to maximize the amount of plastic collected while balancing time and vehicle capacity constraints. This selection process accounts for daily variations in waste generation. The final step involves computing the most efficient travel route for the selected points using a shortest-path algorithm. This minimizes fuel consumption and travel time, helping to lower environmental impact and operational expenses.

The proposed approach incorporates real-time data on plastic quantities and traffic conditions and is implemented using open-source software tools. A real-world case study involving 152 collection points in Bangkok over a 10-day period demonstrated notable improvements in both collection efficiency and route optimization. This contributes to the project’s environmental and financial sustainability.