城市固体废物管理使用多个处置地点-弧形路线和废物分类方法:在英国的现实案例研究

IF 4 Q2 ENGINEERING, INDUSTRIAL
Fatemeh Hirbod, Tourandokht Karimi, Zahra Mohammadnazari, Masoud Rabbani, Amir Aghsami
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引用次数: 0

摘要

摘要:在城市运营领域,城市固体废物(MSW)的有效管理是一项关键的工作。它需要大量分配固定和可变资源以及财政投资。这些支出的大部分与包括废物收集、运输和处置在内的业务方面有关。本研究在考虑车辆容量限制及纳入废物分类的情况下,深入探讨多处置地点弧线路线问题(LARP)。LARP模型的设计目的是确定废物处理场和三个废物处理场的最佳位置。LARP模型的优化目标和约束是为了提高废物收集效率和最小化成本。此外,还引入了一个三角模糊参数来表示需求。为了对该模型进行测试,我们在英国进行了一个真实的案例研究,以评估其性能和实用性。最后,进行了一系列敏感性分析,在不同条件下提供了有价值的管理见解。将废物分类纳入该废物管理模型对管理人员具有相当重要的意义。这是特别相关的,因为它提出了在处理不同类型的废物时更有效的废物管理战略。关键词:选址、路径问题、城市垃圾场、垃圾收集、垃圾分类、数学模型、模糊披露声明、作者未报告潜在利益冲突。数据和材料的可用性由于这项研究的性质,数据在文本中是可用的。作者声明在撰写本文期间没有收到任何资金、资助或其他支持。作者简介:fathemeh Hirbod,德黑兰大学工程学院工业工程学院工业工程硕士。她的主要科学兴趣包括运筹学、废物管理、医疗优化、数学建模。Tourandokht Karimi是德黑兰大学工程学院工业工程学院工业工程硕士。她的主要科学兴趣包括运筹学、机器学习、废物管理、数学建模。Zahra Mohammadnazari,现任英国考文垂大学考文垂商学院战略与领导力学院助理讲师兼博士研究生。在《环境、发展与可持续》、《国际医院研究杂志》、《环境智能与人性化计算杂志》、《多媒体工具与应用》等国际期刊上发表多篇论文。她的主要科学兴趣包括运筹学、多边平台、机器学习、数学建模、组织评估、供应链管理和数据驱动优化。马苏德·拉巴尼(Masoud Rabbani)是德黑兰大学工程学院工业与系统工程学院工业工程教授。在《欧洲运筹学杂志》、《国际生产研究杂志》、《国际生产经济学杂志》、《社会经济计划科学》、《工业与生产工程杂志》等国际期刊上发表论文300余篇。他目前的研究方向包括生产计划(精益生产、综合生产计划)、库存管理系统设计、人道主义物流、图论在工业规划中的应用、生产力管理、EFQM及相关学科。Amir Aghsami是Khaje Nasir Toosi理工大学工业工程学院工业工程博士。他在伊朗德黑兰大学获得工业工程硕士学位。他目前是德黑兰大学工程学院工业与系统工程学院的高级研究员。他在国际期刊上发表了70多篇论文,如社会经济计划科学、计算机与工业工程、国际生产研究杂志、清洁生产杂志、IISE医疗保健系统工程交易等。他的主要科学兴趣包括排队理论、随机过程、运筹学、医疗优化、排队库存系统、数学建模、供应链管理、灾害管理、废物管理和库存控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Municipal solid waste management using multiple disposal location-arc routing and waste segregation approach: a real-life case study in England
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.
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CiteScore
7.50
自引率
6.70%
发文量
21
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