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dc.contributor.authorBlanco Suárez, Víctor 
dc.contributor.authorHijonosa, Yolanda
dc.contributor.authorZavala, Víctor M.
dc.date.accessioned2024-07-18T11:24:08Z
dc.date.available2024-07-18T11:24:08Z
dc.date.issued2024-05-22
dc.identifier.citationBlanco, V. Hinojosa Y. Zavala, V.M. ACS Sustainable Chem. Eng. 2024, 12, 8453−8466. [https://doi.org/10.1021/acssuschemeng.4c01429]es_ES
dc.identifier.urihttps://hdl.handle.net/10481/93228
dc.description.abstractIn this paper, we propose a new mathematical optimization approach to make decisions on the optimal design of the complex logistic system required to produce biogas from waste. We provide a novel and flexible decision-aid tool that allows decision makers to optimally determine the locations of different types of plants (pretreatment, anaerobic digestion, and biomethane liquefaction plants) and pipelines involved in the logistic process, according to a given budget, as well as the most efficient distribution of the products (from waste to biomethane) along the supply chain. The method is based on a mathematical optimization model that we further analyze and that, after reducing the number of variables and constraints without affecting the solutions, is able to solve real-size instances in reasonable CPU times. The proposed methodology is designed to be versatile and adaptable to different situations that arise in the transformation of waste to biogas. The results of our computational experiments, both in synthetic and in a case study instance, prove the validity of our proposal in practical applications. Synthetic instances with up to 200 farms and potential locations for pretreatment plants and 100 potential locations for anaerobic digestion and biomethane liquefaction plants were solved, exactly, within <20 min, whereas the larger instances with 500 farms were solved within <2 h. The CPU times required to solve the real-world instance range from 2 min to 6 h, being highly affected by the given budget to install the plants and the percent of biomethane that is required to be injected in the existing gas network.es_ES
dc.description.sponsorshipPID2020-114594GB-C21, funded by MICIU/AEI/10.13039/ 501100011033, and Grant No. RED2022-134149-T, funded by MICIU/AEI/10.13039/501100011033 (Thematic Network on Location Science and Related Problems)es_ES
dc.description.sponsorshipFEDER +Junta de Andalucía Project Nos. C-EXP-139-UGR23es_ES
dc.description.sponsorshipAT 21_00032; VII PPIT-US (Ayudas Estancias Breves, Modalidad III.2A); and the IMAG-Maria de Maeztu (Grant No. CEX2020-001105-M/AEI/10.13039/501100011033)es_ES
dc.language.isoenges_ES
dc.publisherACS publicationses_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectLogistics, es_ES
dc.subjectGreen Energyes_ES
dc.subjectFacility Locationes_ES
dc.titleThe Waste-to-Biomethane Logistic Problem: A Mathematical Optimization Approaches_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1021/acssuschemeng.4c01429
dc.type.hasVersionVoRes_ES


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