CONICET | Buscador de Institutos y Recursos Humanos

This article presents computational intelligence methods forsolving the problem of locating garbage accumulation points in urbanscenarios, which is a relevant problem in nowadays smart cities to optimizebudget and reduce negative environmental and social impacts.The problem model considers reducing the investment costs, enhancethe proportion of citizens served by bins, and the accessibility to the system.A family of heuristics based on the generic PageRank schema and amutiobjective evolutionary algorithm are proposed. Experimental evaluationperformed on real scenarios on the city of Montevideo, Uruguay,demonstrates the eectiveness of the proposed approaches. The methodsallow computing plannings with dierent trade-o between the problemobjectives and improving over the current planning.