Fatemeh Hirbod, Tourandokht Karimi, Zahra Mohammadnazari, Masoud Rabbani, Amir Aghsami
{"title":"Municipal solid waste management using multiple disposal location-arc routing and waste segregation approach: a real-life case study in England","authors":"Fatemeh Hirbod, Tourandokht Karimi, Zahra Mohammadnazari, Masoud Rabbani, Amir Aghsami","doi":"10.1080/21681015.2023.2265925","DOIUrl":null,"url":null,"abstract":"ABSTRACTIn the realm of municipal operations, the effective management of municipal solid waste (MSW) stands out as a pivotal undertaking. It necessitates substantial allocations of fixed and variable resources and financial investments. The bulk of these expenditures are associated with the operational facets encompassing waste collection, transportation, and disposal. This research delves into the examination of multiple Disposal Location Arc Routing Problems (LARP) while considering vehicle capacity limitations and the incorporation of waste segregation. The LARP model is designed to identify the optimal locations for depots and three waste disposal sites. The optimization objectives and constraints applied to the LARP model are geared toward enhancing waste collection efficiency and minimizing costs. Additionally, a triangular fuzzy parameter is introduced to represent the demand. To put this model to the test, a real-world case study in the UK is explored to evaluate its performance and practicality. Finally, a series of sensitivity analyses are conducted, offering valuable managerial insights under varying conditions. The inclusion of waste segregation in this waste management model holds considerable significance for managers. This is particularly relevant because it proposes a more effective strategy for waste management when dealing with diverse types of waste.KEYWORDS: Location arc routing problemsmunicipal disposal siteswaste collectionwaste segregationmathematical modelfuzzy Disclosure statementNo potential conflict of interest was reported by the authors.Availability of data and materialDue to the nature of this research, data is available within the text.Additional informationFundingThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.Notes on contributorsFatemeh HirbodFathemeh Hirbod is an MSc in Industrial Engineering at the School of Industrial Engineering, College of Engineering, University of Tehran. Her main scientific interests include operations research, waste management, healthcare optimization, mathematical modeling.Tourandokht KarimiTourandokht Karimi is an MSc in Industrial Engineering at the School of Industrial Engineering, College of Engineering, University of Tehran. Her main scientific interests include operations research, machine learning, waste management, mathematical modeling.Zahra MohammadnazariZahra Mohammadnazari is currently an assistant lecturer and PhD candidate at Coventry Business College- School of strategy and leadership, Coventry University, United Kingdom. She has several papers in international journals such as Environment, Development and Sustainability, International Journal of Hospital Research, Journal of Ambient Intelligence and Humanized Computing, Multimedia Tools and Applications, etc. Her main scientific interests include operations research, multi-sided platform, machine learning, mathematical modeling, organizational assessment, supply chain management, and data-driven optimization.Masoud RabbaniMasoud Rabbani is a Professor of Industrial Engineering at the School of Industrial and Systems Engineering, College of Engineering, University of Tehran. He has published more than 300 papers in international journals, such as European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, Socio-economic planning science, Journal of Industrial and Production Engineering, etc. His current research interests comprise production planning (lean production, integrated production planning), design of inventory management systems, humanitarian logistics, applied graph theory in industrial planning, productivity management, EFQM and related subjects.Amir AghsamiAmir Aghsami is a Ph.D. in Industrial Engineering at the School of Industrial Engineering, Khaje Nasir Toosi University of Technology. He received his MS in Industrial engineering from University of Tehran, Iran. He is currently a senior research fellow at the School of Industrial and Systems Engineering, College of Engineering, University of Tehran. He has published more than 70 papers in international journals such as Socio-Economic Planning Sciences, Computer and industrial engineering, International Journal of Production Research, Journal of Cleaner Production, IISE Transactions on Healthcare Systems Engineering, etc. His main scientific interests include queueing theory, stochastic process, operations research, healthcare optimization, queueing inventory systems, mathematical modeling, supply chain management, disaster management, waste management, and inventory control.","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":"248 1","pages":"0"},"PeriodicalIF":4.0000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial and Production Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/21681015.2023.2265925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACTIn the realm of municipal operations, the effective management of municipal solid waste (MSW) stands out as a pivotal undertaking. It necessitates substantial allocations of fixed and variable resources and financial investments. The bulk of these expenditures are associated with the operational facets encompassing waste collection, transportation, and disposal. This research delves into the examination of multiple Disposal Location Arc Routing Problems (LARP) while considering vehicle capacity limitations and the incorporation of waste segregation. The LARP model is designed to identify the optimal locations for depots and three waste disposal sites. The optimization objectives and constraints applied to the LARP model are geared toward enhancing waste collection efficiency and minimizing costs. Additionally, a triangular fuzzy parameter is introduced to represent the demand. To put this model to the test, a real-world case study in the UK is explored to evaluate its performance and practicality. Finally, a series of sensitivity analyses are conducted, offering valuable managerial insights under varying conditions. The inclusion of waste segregation in this waste management model holds considerable significance for managers. This is particularly relevant because it proposes a more effective strategy for waste management when dealing with diverse types of waste.KEYWORDS: Location arc routing problemsmunicipal disposal siteswaste collectionwaste segregationmathematical modelfuzzy Disclosure statementNo potential conflict of interest was reported by the authors.Availability of data and materialDue to the nature of this research, data is available within the text.Additional informationFundingThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.Notes on contributorsFatemeh HirbodFathemeh Hirbod is an MSc in Industrial Engineering at the School of Industrial Engineering, College of Engineering, University of Tehran. Her main scientific interests include operations research, waste management, healthcare optimization, mathematical modeling.Tourandokht KarimiTourandokht Karimi is an MSc in Industrial Engineering at the School of Industrial Engineering, College of Engineering, University of Tehran. Her main scientific interests include operations research, machine learning, waste management, mathematical modeling.Zahra MohammadnazariZahra Mohammadnazari is currently an assistant lecturer and PhD candidate at Coventry Business College- School of strategy and leadership, Coventry University, United Kingdom. She has several papers in international journals such as Environment, Development and Sustainability, International Journal of Hospital Research, Journal of Ambient Intelligence and Humanized Computing, Multimedia Tools and Applications, etc. Her main scientific interests include operations research, multi-sided platform, machine learning, mathematical modeling, organizational assessment, supply chain management, and data-driven optimization.Masoud RabbaniMasoud Rabbani is a Professor of Industrial Engineering at the School of Industrial and Systems Engineering, College of Engineering, University of Tehran. He has published more than 300 papers in international journals, such as European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, Socio-economic planning science, Journal of Industrial and Production Engineering, etc. His current research interests comprise production planning (lean production, integrated production planning), design of inventory management systems, humanitarian logistics, applied graph theory in industrial planning, productivity management, EFQM and related subjects.Amir AghsamiAmir Aghsami is a Ph.D. in Industrial Engineering at the School of Industrial Engineering, Khaje Nasir Toosi University of Technology. He received his MS in Industrial engineering from University of Tehran, Iran. He is currently a senior research fellow at the School of Industrial and Systems Engineering, College of Engineering, University of Tehran. He has published more than 70 papers in international journals such as Socio-Economic Planning Sciences, Computer and industrial engineering, International Journal of Production Research, Journal of Cleaner Production, IISE Transactions on Healthcare Systems Engineering, etc. His main scientific interests include queueing theory, stochastic process, operations research, healthcare optimization, queueing inventory systems, mathematical modeling, supply chain management, disaster management, waste management, and inventory control.