DC FieldValueLanguage
dc.contributor.authorAnagnostopoulos, Theodoros-
dc.contributor.authorBehdad, Sara-
dc.contributor.authorShah, Parth Jatinkumar-
dc.contributor.authorZaslavsky, Arkady-
dc.date.accessioned2024-07-05T06:54:06Z-
dc.date.available2024-07-05T06:54:06Z-
dc.date.issued2018-08-01-
dc.identifierscopus-85047440899-
dc.identifier.issn1879-2456-
dc.identifier.issn0956-053X-
dc.identifier.other85047440899-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2666-
dc.description.abstractThe 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.isoenen_US
dc.relation.ispartofWaste Managementen_US
dc.subjectChance-constrained programmingen_US
dc.subjectEnd-of-life recoveryen_US
dc.subjectIoT-enabled waste collection and recoveryen_US
dc.subjectSmart citiesen_US
dc.titleA stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable citiesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.wasman.2018.05.019en_US
dc.identifier.scopus2-s2.0-85047440899-
dcterms.accessRights1en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume78en_US
dc.identifier.spage104en_US
dc.identifier.epage114en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0002-5587-2848-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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