DC Field | Value | Language |
---|---|---|
dc.contributor.author | Anagnostopoulos, Theodoros | - |
dc.contributor.author | Behdad, Sara | - |
dc.contributor.author | Shah, Parth Jatinkumar | - |
dc.contributor.author | Zaslavsky, Arkady | - |
dc.date.accessioned | 2024-07-05T06:54:06Z | - |
dc.date.available | 2024-07-05T06:54:06Z | - |
dc.date.issued | 2018-08-01 | - |
dc.identifier | scopus-85047440899 | - |
dc.identifier.issn | 1879-2456 | - |
dc.identifier.issn | 0956-053X | - |
dc.identifier.other | 85047440899 | - |
dc.identifier.uri | https://uniwacris.uniwa.gr/handle/3000/2666 | - |
dc.description.abstract | The concept of City 2.0 or smart city is offering new opportunities for handling waste management practices. The existing studies have started addressing waste management problems in smart cities mainly by focusing on the design of new sensor-based Internet of Things (IoT) technologies, and optimizing the routes for waste collection trucks with the aim of minimizing operational costs, energy consumption and transportation pollution emissions. In this study, the importance of value recovery from trash bins is highlighted. A stochastic optimization model based on chance-constrained programming is developed to optimize the planning of waste collection operations. The objective of the proposed optimization model is to minimize the total transportation cost while maximizing the recovery of value still embedded in waste bins. The value of collected waste is modeled as an uncertain parameter to reflect the uncertain value that can be recovered from each trash bin due to the uncertain condition and quality of waste. The application of the proposed model is shown by using a numerical example. The study opens new venues for incorporating the value recovery aspect into waste collection planning and development of new data acquisition technologies that enable municipalities to monitor the mix of recyclables embedded in individual trash bins. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Waste Management | en_US |
dc.subject | Chance-constrained programming | en_US |
dc.subject | End-of-life recovery | en_US |
dc.subject | IoT-enabled waste collection and recovery | en_US |
dc.subject | Smart cities | en_US |
dc.title | A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/j.wasman.2018.05.019 | en_US |
dc.identifier.scopus | 2-s2.0-85047440899 | - |
dcterms.accessRights | 1 | en_US |
dc.relation.dept | Department of Business Administration | en_US |
dc.relation.faculty | School of Administrative, Economics and Social Sciences | en_US |
dc.relation.volume | 78 | en_US |
dc.identifier.spage | 104 | en_US |
dc.identifier.epage | 114 | en_US |
dc.collaboration | University of West Attica (UNIWA) | en_US |
dc.journals | Open Access | en_US |
dc.publication | Peer Reviewed | en_US |
dc.country | Greece | en_US |
local.metadatastatus | verified | en_US |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | Department of Business Administration | - |
crisitem.author.faculty | School of Administrative, Economics and Social Sciences | - |
crisitem.author.orcid | 0000-0002-5587-2848 | - |
crisitem.author.parentorg | School of Administrative, Economics and Social Sciences | - |
Appears in Collections: | Articles / Άρθρα |
CORE Recommender
SCOPUSTM
Citations
80
checked on Dec 17, 2024
Page view(s)
19
checked on Dec 22, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.