The Optimization of the Service Meeting Locations for the Safe Return-home Service of Seoul Using the MCLP Model

This public safety service ensures the safe return of citizens at night by having scouts accompany them on foot to their residences. However, the current service suffers from a lack of demand forecasting in the selection of supply points. This project addresses this limitation by predicting actual service demand and reselecting supply points to improve operational efficiency. Specifically, the meeting points where scouts and users begin the service were optimized using the Maximal Covering Location Problem (MCLP) model. This approach enabled the service to cover a broader area with the same human resources, enhancing its effectiveness.