A mixed integer linear programming model for long-term planning of municipal solid waste management systems: Against restricted mass balances

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dc.authorid0000-0002-0617-5245en_US
dc.contributor.authorBatur, Maliki Ejder
dc.contributor.authorCihan, Ahmet
dc.contributor.authorKorucu, Mahmut Kemal
dc.contributor.authorBektas, Nihal
dc.contributor.authorKeskinler, Bulent
dc.date.accessioned2021-03-20T20:09:32Z
dc.date.available2021-03-20T20:09:32Z
dc.date.issued2020
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Çevre Mühendisliği Bölümüen_US
dc.description.abstractLong-term planning of municipal solid waste management systems is a complex decision making problem which includes a large number of decision layers. Since all different waste treatment and disposal processes will show different responses to each municipal solid waste component, it is necessary to separately evaluate all waste components for all processes. This obligation creates an obstacle in the programming of mass balances for long-term planning of municipal solid waste management systems. The development of an ideal mixed integer linear programming model that can simultaneously respond to all essential decision layers including waste collection, process selection, waste allocation, transportation, location selection, and capacity assessment has not been made possible yet due to this important modeling obstacle. According to the current knowledge of the literature, all mixed integer linear programming studies aiming to address this obstacle so far have had to restrict many different possibilities in their mass balances. In this study, a novel mixed integer linear programming model was formulated. ALOMWASTE, the new model structure developed in this study, was built to take into consideration different process, capacity, and location possibilities that may occur in complex waste management processes at the same time. The results obtained from a case study showed the feasibility of new mixed integer linear programming model obtained in this study for the simultaneous solution of all essential decision layers in an unrestricted mass balance. The model is also able to provide significant convenience for the multi-objective optimization of financial-environmental-social costs and the solution of some uncertainty problems of decision-making tools such as life cycle assessment. (C) 2020 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.wasman.2020.02.003en_US
dc.identifier.endpage222en_US
dc.identifier.issn0956-053X
dc.identifier.issn1879-2456
dc.identifier.pmid32087539en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage211en_US
dc.identifier.urihttp://doi.org/10.1016/j.wasman.2020.02.003
dc.identifier.urihttps://hdl.handle.net/20.500.12885/454
dc.identifier.volume105en_US
dc.identifier.wosWOS:000520856700021en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorKorucu, Mahmut Kemal
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofWaste Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCost optimizationen_US
dc.subjectDecision-makingen_US
dc.subjectMathematical modelingen_US
dc.subjectMunicipal solid wastesen_US
dc.titleA mixed integer linear programming model for long-term planning of municipal solid waste management systems: Against restricted mass balancesen_US
dc.typeArticleen_US

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