A method for optimizing waste collection using mathematical programming: a Buenos Aires case study

Abstract

A method is proposed that uses operations research techniques to optimize the routes of waste collection vehicles servicing dumpster or skip-type containers. The waste collection problem is reduced to the classic travelling salesman problem, which is then solved using the Concorde solver program. A case study applying the method to the collection system in the southern zone of Buenos Aires is also presented. In addition to the typical minimum distance criterion, the optimization problem incorporates the objective of reducing vehicle wear and tear as measured by the physics concept of mechanical work. The solution approach, employing graph theory and mathematical programming tools, is fully described and the data correction process is also discussed. The application of the proposed method minimized the distance travelled by each collection vehicle in the areas studied, with actual reductions ranging from 10 to 40% of the existing routes. The shortened distances led in turn to substantial decreases in work done and therefore in vehicle wear and tear. Extrapolation of the results to the entire southern zone of Buenos Aires indicates potential savings for the civic authorities of more than US $200,000 per year in addition to the qualitative impacts of less traffic disruption, less vehicle driver fatigue and less pollution.