Developing Optimization Tools for Municipal Solid Waste Collection in the Argentine City of Berazategui

Abstract

We apply mathematical and computational techniques to the development of an approach for optimizing the waste collection system of the Argentine city of Berazategui, 26 km south of Buenos Aires. Taking full account of the city’s particular characteristics, our objective is to not only improve the system’s efficiency but also ensure equitable workloads for waste collection truck crews, both drivers and collectors. The optimization problem is partitioned into three stages. In the first stage, a heuristic constructs structurally simple collection zones that are balanced in terms of collectors’ walking distances. In the second stage, a mixed integer linear programming model designs a collection truck route for each zone and minimizes its length. In the third and final stage, each truck is assigned to two zones in such a way as to equalize to the extent possible the length of drivers’ working day. Since working day length is influenced by multiple factors, we formulate this objective as a bi-objective optimization problem and solve it by integer linear programming coupled with an iterative algorithm. The city implemented the approach in early 2020, resulting in a marked more equitable workload distribution and significant fuel savings and maintenance expense for the city.