Solving The Automated Vacuum Waste Collection Optimization Problem

Automated vacuum waste collection (AVWC) uses air suction on a closed network of underground pipes to transport waste from the drop off points scattered throughout the city to a central collection point, reducing greenhouse gas emissions and the inconveniences of conventional methods (odors, noise, . . . ). Since a significant part of the cost of operating AVWC systems is energy consumption, we have started a project with the aim of applying constraint programming technology to schedule the daily emptying sequences of the drop off points in such a way that energy consumption is minimized. In this paper we define AVWC systems, encode the problem of deciding the drop off points that should be emptied at a given time as a constraint integer programming (CIP) problem, and empirically evaluate our approach with real data. Our paper is a step forward in solving the challenge posed in [1], and extends the results of [2] by dealing with a limited but complete set of sectors, and by making decisions taking into account subsectors instead of individual drop off points. This way, we obtain simpler models that achieve good quality real-time solutions. Furthermore, we include experiments with real data that were beyond the reach of [2].