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Title:
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Approximate dynamic programming for automated vacuum waste collection systems
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Author:
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Fernàndez Camon, César; Manyà Serres, Felip; Mateu Piñol, Carles; Solé Mauri, Francina
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Notes:
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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. |
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Subject(s):
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-Urban waste
-Optimization
-machine learning
-AVWCS (Automated Vacuum Waste Collection)
-Smart cities
-Residus
-Waste products |
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Rights:
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(c) Elsevier, 2015
info:eu-repo/semantics/restrictedAccess |
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Document type:
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Article
publishedVersion |
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Published by:
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Elsevier
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Share:
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