{"id":{"repo_id":"gmu","oai_identifier":"oai:MARS:1920/14385"},"canonical_url":"https://search.dev.ndltd.org/etd/gmu/oai:MARS:1920/14385","repository":{"repo_id":"gmu","name":"George Mason University","base_url":"https://mars.gmu.edu/server/oai/request"},"display":{"title":"MULTI-OBJECTIVE DECISION-MAKING FRAMEWORK FOR SMART MUNICIPAL SOLID WASTE MANAGEMENT","abstract":"Due to the explosion of waste generation rate, especially in urban areas, and acceleration of environmental degradation worldwide, waste management turns into one of the critical urban services and a great deal of attention has been devoted to municipal solid waste issues. On the other hand, the rapid development of advanced technologies and the advent of smart waste equipment in recent years, has made it possible to mitigate some of the challenges facing the conventional waste system. To enhance the added value of waste system and measure the influence of modern technologies on municipal solid waste management, many studies have been conducted on smart cities to address the main sustainability issues, such as circular economy, environmental problems, adverse social impacts, and energy consumption. This research aims to introduce a new smart municipal solid waste framework considering three main pillars of sustainability, namely, economic, environmental, and social aspects. To achieve this goal, an integrated multi-objective optimization model is developed to make the waste system more resilient against unexpected situations. Proposing a stochastic optimization model is a key enabler to improve the resiliency of the system. The focus of this study is more on sustainable and renewable energy production than safe disposal of waste materials, which significantly mitigating environmental impacts while yielding financial benefits to waste management systems. In the management of waste operations there are major challenges from transportation and logistics viewpoints, representing some of the most complicated and problematic stages within this domain. To enhance the quality of urban services and the responsiveness of the waste system, particularly in transportation and waste collection phases, this research utilizes Communication and Internet of Things technologies to reveal real needs of citizens and thereby improve the efficiency of waste management system. Moreover, this research contributes to the development of an approximate solution methodology designed to address the dynamic, uncertain, and complex nature of municipal solid waste management. The effectiveness and applicability of the proposed optimization models and solution approaches are assessed through numerical experiments conducted across various dimensions and a case study problem. The outcomes of this research can aid policymakers, practitioners, and local governments in enhancing and maintaining a resilient waste management system. This, in turn, contributes to improved efficiency and sustainability within the waste sector.","abstract_html":"Due to the explosion of waste generation rate, especially in urban areas, and acceleration of environmental degradation worldwide, waste management turns into one of the critical urban services and a great deal of attention has been devoted to municipal solid waste issues. On the other hand, the rapid development of advanced technologies and the advent of smart waste equipment in recent years, has made it possible to mitigate some of the challenges facing the conventional waste system. To enhance the added value of waste system and measure the influence of modern technologies on municipal solid waste management, many studies have been conducted on smart cities to address the main sustainability issues, such as circular economy, environmental problems, adverse social impacts, and energy consumption. This research aims to introduce a new smart municipal solid waste framework considering three main pillars of sustainability, namely, economic, environmental, and social aspects. To achieve this goal, an integrated multi-objective optimization model is developed to make the waste system more resilient against unexpected situations. Proposing a stochastic optimization model is a key enabler to improve the resiliency of the system. The focus of this study is more on sustainable and renewable energy production than safe disposal of waste materials, which significantly mitigating environmental impacts while yielding financial benefits to waste management systems. In the management of waste operations there are major challenges from transportation and logistics viewpoints, representing some of the most complicated and problematic stages within this domain. To enhance the quality of urban services and the responsiveness of the waste system, particularly in transportation and waste collection phases, this research utilizes Communication and Internet of Things technologies to reveal real needs of citizens and thereby improve the efficiency of waste management system. Moreover, this research contributes to the development of an approximate solution methodology designed to address the dynamic, uncertain, and complex nature of municipal solid waste management. The effectiveness and applicability of the proposed optimization models and solution approaches are assessed through numerical experiments conducted across various dimensions and a case study problem. The outcomes of this research can aid policymakers, practitioners, and local governments in enhancing and maintaining a resilient waste management system. This, in turn, contributes to improved efficiency and sustainability within the waste sector.","abstract_has_math":false,"creators":["Hashemi Amiri, Seyed Omid"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024","date_published":"2024","updated_at":"2026-07-27T19:51:44Z","subjects":["Distributionally Robust Optimization","Genetic Algorithm","Multi-Objective Optimization","Municipal Solid Waste Management","Reliability","Sustainability"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/14385"],"render_values":[{"text":"hdl:1920/14385","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2024"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Distributionally Robust Optimization","Genetic Algorithm","Multi-Objective Optimization","Municipal Solid Waste Management","Reliability","Sustainability"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/14385"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["Due to the explosion of waste generation rate, especially in urban areas, and acceleration of environmental degradation worldwide, waste management turns into one of the critical urban services and a great deal of attention has been devoted to municipal solid waste issues. On the other hand, the rapid development of advanced technologies and the advent of smart waste equipment in recent years, has made it possible to mitigate some of the challenges facing the conventional waste system. To enhance the added value of waste system and measure the influence of modern technologies on municipal solid waste management, many studies have been conducted on smart cities to address the main sustainability issues, such as circular economy, environmental problems, adverse social impacts, and energy consumption. This research aims to introduce a new smart municipal solid waste framework considering three main pillars of sustainability, namely, economic, environmental, and social aspects. To achieve this goal, an integrated multi-objective optimization model is developed to make the waste system more resilient against unexpected situations. Proposing a stochastic optimization model is a key enabler to improve the resiliency of the system. The focus of this study is more on sustainable and renewable energy production than safe disposal of waste materials, which significantly mitigating environmental impacts while yielding financial benefits to waste management systems. In the management of waste operations there are major challenges from transportation and logistics viewpoints, representing some of the most complicated and problematic stages within this domain. To enhance the quality of urban services and the responsiveness of the waste system, particularly in transportation and waste collection phases, this research utilizes Communication and Internet of Things technologies to reveal real needs of citizens and thereby improve the efficiency of waste management system. Moreover, this research contributes to the development of an approximate solution methodology designed to address the dynamic, uncertain, and complex nature of municipal solid waste management. The effectiveness and applicability of the proposed optimization models and solution approaches are assessed through numerical experiments conducted across various dimensions and a case study problem. The outcomes of this research can aid policymakers, practitioners, and local governments in enhancing and maintaining a resilient waste management system. This, in turn, contributes to improved efficiency and sustainability within the waste sector."]},{"key":"dc:title","label":"Title","values":["MULTI-OBJECTIVE DECISION-MAKING FRAMEWORK FOR SMART MUNICIPAL SOLID WASTE MANAGEMENT"]}]}],"canonical_facts":{"dc:date.issued":["2024"],"dc:description.other":["Due to the explosion of waste generation rate, especially in urban areas, and acceleration of environmental degradation worldwide, waste management turns into one of the critical urban services and a great deal of attention has been devoted to municipal solid waste issues. On the other hand, the rapid development of advanced technologies and the advent of smart waste equipment in recent years, has made it possible to mitigate some of the challenges facing the conventional waste system. To enhance the added value of waste system and measure the influence of modern technologies on municipal solid waste management, many studies have been conducted on smart cities to address the main sustainability issues, such as circular economy, environmental problems, adverse social impacts, and energy consumption. This research aims to introduce a new smart municipal solid waste framework considering three main pillars of sustainability, namely, economic, environmental, and social aspects. To achieve this goal, an integrated multi-objective optimization model is developed to make the waste system more resilient against unexpected situations. Proposing a stochastic optimization model is a key enabler to improve the resiliency of the system. The focus of this study is more on sustainable and renewable energy production than safe disposal of waste materials, which significantly mitigating environmental impacts while yielding financial benefits to waste management systems. In the management of waste operations there are major challenges from transportation and logistics viewpoints, representing some of the most complicated and problematic stages within this domain. To enhance the quality of urban services and the responsiveness of the waste system, particularly in transportation and waste collection phases, this research utilizes Communication and Internet of Things technologies to reveal real needs of citizens and thereby improve the efficiency of waste management system. Moreover, this research contributes to the development of an approximate solution methodology designed to address the dynamic, uncertain, and complex nature of municipal solid waste management. The effectiveness and applicability of the proposed optimization models and solution approaches are assessed through numerical experiments conducted across various dimensions and a case study problem. The outcomes of this research can aid policymakers, practitioners, and local governments in enhancing and maintaining a resilient waste management system. This, in turn, contributes to improved efficiency and sustainability within the waste sector."],"dc:identifier":["hdl:1920/14385"],"dc:subject":["Distributionally Robust Optimization","Genetic Algorithm","Multi-Objective Optimization","Municipal Solid Waste Management","Reliability","Sustainability"],"dc:title":["MULTI-OBJECTIVE DECISION-MAKING FRAMEWORK FOR SMART MUNICIPAL SOLID WASTE MANAGEMENT"],"dc:type":["Dissertation"]},"updated_at":"2026-07-27T19:51:44Z"}