Approximate dynamic programming for automated vacuum waste collection systems

The collection and treatment of waste poses a major challenge to modern urban planning, particularly to smart cities. To cope with this problem, a cost-effective alternative to conventional methods is the use of Automated Vacuum Waste Collection (AVWC) systems, using 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. This paper describes and empirically evaluates a novel approach to defining daily operation plans for AVWC systems to improve quality of service, and reduce energy consumption, which represents about 60% of the total operation cost. We model a daily AVWC operation as a Markov decision process, and use Approximate Dynamic Programming techniques (ADP) to obtain optimal operation plans. The experiments, comparing our approach with the current approach implemented in some real-world AVWC systems, show that ADP techniques significantly improve the quality of AVWC operation plans. © 2015 Elsevier Ltd.This work has been partially funded by the Generalitat de Catalunya under grant AGAUR 2009-SGR-1434, and the Ministerio de Economía y Competividad research projects CO-PRIVACY (TIN2011-27076-C03-03), ARINF (TIN2009-14704-C03-01/03), TASSAT (TIN2010-20967-C04-01/03), and Newmatica (IPT-2011-1496-310000) from program INNPACTO (funded by the Ministerio de Ciencia y Tecnología until 2011)Peer Reviewe