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Quantity-predictive vehicle routing problem for smart waste collection

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dc.title Quantity-predictive vehicle routing problem for smart waste collection en
dc.contributor.author Hrabec, Dušan
dc.contributor.author Senland, Preben
dc.contributor.author Nevrlý, Vlastimír
dc.contributor.author Popela, Pavel
dc.contributor.author Hoff, Arild
dc.contributor.author Šomplák, Radovan
dc.contributor.author Pavlas, Martin
dc.relation.ispartof Chemical Engineering Transactions
dc.identifier.issn 2283-9216 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2019
utb.relation.volume 76
dc.citation.spage 1249
dc.citation.epage 1254
dc.type article
dc.language.iso en
dc.publisher Italian Association of Chemical Engineering - AIDIC
dc.identifier.doi 10.3303/CET1976209
dc.relation.uri https://www.aidic.it/cet/19/76/209.pdf
dc.description.abstract The current trends in the field of waste management involves the use of modern technologies such as wireless sensors. The smart waste management with Sensor Technology involves an integration of the so-called smart trash bins and containers into existing network by using sensors that fill level of the bins and containers. Apart from the technological aspects of the problem, this arrangement points to the need of development of new decision-making tools that allow collectors to make fast and smart operative decisions on the waste collection. The sensors from the waste containers read the current fill-height once a day and send the information to the central database. The central decision-maker appraises the data and makes the waste collection plan for an entire (e.g., one week) collection period; note that this improves existing models on the data available and used. The aim of this paper is to present complex modelling ideas, develop a simple mathematical model, discuss its complexity and propose/discuss a computational approach in order to solve the collection problem. The objective is to optimize the dynamic planning on daily garbage-truck schedules with respect to minimization of transportation costs that also reflects a positive environmental impact presented by savings in transportation/routing distance. The secondary objective is to optimally decide on early collection of partly-filled containers, especially those directly on or close to the optimum route linking the full ones considering waste production rates in the next days. The paper outlines some directions for further research such as the need of modifying the old-existing models into a form utilizing the newly available data. This leads to specific vehicle routing problems that request appropriate computational time requirements and the need of suitable heuristic methods development. Copyright © 2019, AIDIC Servizi S.r.l. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009501
utb.identifier.obdid 43880999
utb.identifier.scopus 2-s2.0-85076310449
utb.source j-scopus
dc.date.accessioned 2020-01-07T08:12:38Z
dc.date.available 2020-01-07T08:12:38Z
utb.contributor.internalauthor Hrabec, Dušan
utb.fulltext.affiliation Dušan Hrabec a*, Preben Senland b, Vlastimír Nevrlý c, Pavel Popela d, Arild Hoff b, Radovan Šomplák c, Martin Pavlas c a Faculty of Applied Informatics, Tomas Bata University in Zlín, T.G. Masaryka 5555, 760 01 Zlín, Czech Republic b Molde University College – Specialized University in Logistics, Britvegen 2, 6410 Molde, Norway c Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology – VUT Brno, Technická 2896/2, 616 69 Brno, Czech Republic d Institute of Mathematics, Faculty of Mechanical Engineering, Brno University of Technology – VUT Brno, Technická 2896/2, 616 69 Brno, Czech Republic hrabec@utb.cz
utb.fulltext.dates Received: 15/03/2019 Revised: 30/04/2019 Accepted: 02/05/2019
utb.fulltext.sponsorship The authors gratefully acknowledge financial support provided by ERDF within the research project No. CZ.02.1.01/0.0/0.0/16_026/0008413 "Strategic Partnership for Environmental Technologies and Energy Production" and by the project “Computer Simulations for Effective Low-Emission Energy” funded as project No. CZ.02.1.01/0.0/0.0/16 026/0008392 by Operational Programme Research, Development and Education, Priority axis 1: Strengthening capacity for high-quality research.
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlín, T.G. Masaryka 5555, Zlín, 760 01, Czech Republic; Molde University College – Specialized University in Logistics, Britvegen 2, Molde, 6410, Norway; Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, VUT Brno, Technická 2896/2, Brno, 616 69, Czech Republic; Institute of Mathematics, Faculty of Mechanical Engineering, Brno University of Technology, VUT Brno, Technická 2896/2, Brno, 616 69, Czech Republic
utb.fulltext.projects CZ.02.1.01/0.0/0.0/16_026/0008413
utb.fulltext.projects CZ.02.1.01/0.0/0.0/16 026/0008392
utb.fulltext.faculty Faculty of Applied Informatics
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