Optimization Model for Collaborative Location–Allocation of Recyclable Household Solid Waste: A Case Study in Cerro Navia and Quinta Normal, Chile

Abstract

This study applies a mixed-integer linear programming model to solve the location-allocation problem for recyclable household waste bins in the communes of Cerro Navia and Quinta Normal, Santiago, Chile. The model determines optimal bin placement in public spaces and assigns residents to collection sites within a maximum walking distance. Three scenarios are evaluated: individual planning for each commune and a collaborative scenario promoting inter-municipal cooperation. Results show that collaboration reduces infrastructure costs by 1.2% (USD $2,400) while improving average walking distance by 4.6% and increasing bin utilization from 85\% to 87.3%. Sensitivity analysis reveals that participation rate drives system scale linearly, while maximum bins per site is not a binding constraint. Collaboration generates savings at all participation levels tested. The findings suggest that joint optimization of collection networks across municipal boundaries can improve both cost efficiency and service accessibility without additional investment.