Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113536
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorWan, M-
dc.creatorQu, T-
dc.creatorHuang, GQ-
dc.creatorChen, RH-
dc.creatorHuang, MN-
dc.creatorPan, YH-
dc.creatorNie, DX-
dc.creatorChen, JR-
dc.date.accessioned2025-06-10T08:56:31Z-
dc.date.available2025-06-10T08:56:31Z-
dc.identifier.urihttp://hdl.handle.net/10397/113536-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wan, M., Qu, T., Huang, G. Q., Chen, R., Huang, M., Pan, Y., Nie, D., & Chen, J. (2024). A Bi-Objective Model for the Location and Optimization Configuration of Kitchen Waste Transfer Stations. Systems, 12(12), 571 is available at https://dx.doi.org/10.3390/systems12120571.en_US
dc.subjectKitchen wasteen_US
dc.subjectLocation of transfer stationen_US
dc.subjectResource configuration optimizationen_US
dc.subjectBi-objective optimizationen_US
dc.subjectImproved NSGA-IIen_US
dc.titleA bi-objective model for the location and optimization configuration of kitchen waste transfer stationsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume12-
dc.identifier.issue12-
dc.identifier.doi10.3390/systems12120571-
dcterms.abstractSince the implementation of China's mandatory waste sorting policy, the recycling of kitchen waste has become one of the core tasks of waste classification. The problem of designing the locations and the optimization configuration strategy for kitchen waste transfer stations faces great challenges in reconstructing the municipal solid waste collection and transportation system. This paper establishes an integer programming model for the bi-objectives of the location and optimal configuration for a kitchen waste transfer station, with the goal of minimizing the total cost and overall negative environmental impact. An improved non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) is used to solve the problem, resulting in a Pareto-optimal solution set that includes several non-dominated solutions, thereby providing diversified choices for decision-makers. Finally, a pilot case involving cooperative enterprises is used as an example in this study, and the results demonstrate the effectiveness of the model and algorithm, as well as their feasibility in practice.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSystems, Dec. 2024, v. 12, no. 12, 571-
dcterms.isPartOfSystems-
dcterms.issued2024-12-
dc.identifier.isiWOS:001386778300001-
dc.identifier.eissn2079-8954-
dc.identifier.artn571-
dc.description.validate202506 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; National Key Research and Development Program of China; 2019 Guangdong Special Support Talent Program—Innovation and Entrepreneurship Leading Team (China); 2018 Guangzhou Leading Innovation Team Program (China); the Science and Technology Development Fund (Macau SAR); the Fundamental Research Funds for the Central Universitiesen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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