Reverse logistics management of used Nickel Manganese Cobalt (NMC) batteries is a key challenge in supporting sustainability and the circular economy in Indonesia. PT XYZ, as a distributor, faces the issue of determining optimal collection points to minimize transportation costs. This study develops a Mixed Integer Linear Programming (MILP) model to optimize the location of used NMC battery collection points within PT XYZ’s distribution network, assuming that consumers are willing to deliver the batteries themselves. A quantitative approach is applied using primary data from expert interviews and secondary data from Google Maps and the Central Bureau of Statistics (BPS), focusing on West Java due to its high vehicle count and population. The model incorporates variables such as demand volume, dealer capacity, and inter-regional distances, with an objective function to minimize total transportation costs while meeting all demands. Implemented using Google Colab and the PuLP library, the model was verified and validated through five debugging runs and sensitivity analysis on cost and capacity parameters. Results show that the model effectively identifies 18 optimal dealer locations that can accommodate 23,772 requests without exceeding capacity, while minimizing transport distances. This approach proves effective in supporting reverse logistics and generating economic value from battery waste, offering a scalable solution and policy basis for sustainable battery waste management in Indonesia.