DocumentCode
1904000
Title
Optimizing Energy Consumption in Automated Vacuum Waste Collection Systems
Author
Bejar, R. ; Fernandez, Camino ; Manya, F. ; Mateu, C. ; Sole-Mauri, F.
Author_Institution
Dept. of Comput. Sci., Univ. de Lleida, Lleida, Spain
Volume
1
fYear
2012
fDate
7-9 Nov. 2012
Firstpage
291
Lastpage
298
Abstract
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, together with a company that builds and installs such systems, 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 describe how the problem of deciding the drop off points that should be emptied at a given time can be modeled as a constraint integer programming (CIP) problem. Moreover, we report on experiments using real data from AVWC systems installed in different cities that provide empirical evidence that CIP offers a suitable technology for reducing energy consumption in AVWC.
Keywords
air pollution; constraint handling; energy conservation; energy consumption; integer programming; minimisation; pipes; vacuum apparatus; waste disposal; waste handling; AVWC systems; CIP problem; automated vacuum waste collection systems; central collection point; constraint integer programming problem; drop off point daily emptying sequences; energy consumption minimization; energy consumption optimization; greenhouse gas emission reduction; underground pipes; waste transportation; Atmospheric modeling; Cities and towns; Energy consumption; Junctions; Linear programming; Programming; Valves;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on
Conference_Location
Athens
ISSN
1082-3409
Print_ISBN
978-1-4799-0227-9
Type
conf
DOI
10.1109/ICTAI.2012.47
Filename
6495059
Link To Document