Integrated Municipal Solid Waste Management under uncertainty: A tri-echelon city logistics and transportation context

Asefi, Hossein; Shahparvari, Shahrooz; Chhetri, Prem

doi:10.1016/j.scs.2019.101606

Cited by 44 publications

(49 citation statements)

References 33 publications

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“…Similarly, Rahimi et al (2020) proposed a decision support system for site location of landfill considering sustainable aspects including environmental, economic, and social criteria. Asefi et al (2019) proposed a two-stage stochastic optimization approach to effectively support the cost-effective WM transportation system by determining the optimal fleet size and decomposition, vehicles routes and capacity-allocation to the system components. Bui et al (2020) studied effective municipal solid waste management capability under uncertainty in Vietnam.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

Valizadeh

Aghdamigargari

Jamali

et al. 2021

Journal of Cleaner Production

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The COVID-19 virus in a short time has caused a terrible crisis that has been spread around the world. This crisis has affected human life in several dimensions, one of which is a sharp increase in urban waste. This increase in waste volume during the pandemic, in addition to the intense increase in costs associated with the risks of virus contagion through infectious waste. In this study, a hybrid mathematical modelling approach including a Bi-level programming model for infectious waste management has been proposed. At the higher level of the model, government decisions regarding the total costs related to infectious waste must be minimized. At this level, the collected infectious waste is converted into energy, the revenue of which is returned to the system. The lower level relates to the risks of virus contagion through infectious waste, which can be catastrophic if ignored. This study has considered the low, medium, high and very high prevalence scenarios as key parameters for the production of waste. In addition, the uncertainty in citizens’ demand for waste collection was also included in the proposed model. The results showed that by energy production from waste during the COVID-19 pandemic, 34% of the total cost of collecting and transporting waste can be compensated. Finally, this paper obtained useful managerial insights using the data of Kermanshah city as a real case.

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

Valizadeh

Aghdamigargari

Jamali

et al. 2021

Journal of Cleaner Production

View full text Add to dashboard Cite

show abstract

“…This approach was improved based on previous time interval linear programming (ILP), FLP and T2 FLP and tackled ambiguous matters in the field of MSWM. By considering uncertainty in production ratios of MSW, Asefi et al (2019) proposed a two-stage stochastic optimization approach for efficient support of the economical ISWM of the transport system through determining the size and optimal decomposition of the special fleet, vehicle routes and capacity allocation to system components. Caldeira et al (2016) attempted to reduce the cost and environmental impact of biodiesel compared to other virgin oil, as a raw material for biodiesel production by incorporating uncertainty in the biodiesel life cycle assessment of cooking oil waste.…”

Section: Waste Collection Under Uncertaintymentioning

confidence: 99%

A novel cooperative model in the collection of infectious waste in COVID-19 pandemic

Valizadeh

Mozafari

2021

JM2

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Purpose Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors. Design/methodology/approach Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time. Findings The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model. Originality/value The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

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“…Some scholars took MSW logistics planning and transportation costs into account, applying Location-Routing Problem (LRP) models to find the optimal MSW allocation. Asefi, Lim, Maghrebi, and Shahparvari [20] took minimize MSW transportation and disposal cost as the objectives to optimize the MSW transportation route and allocation solutions. Khattak [21] et al designed a Cross-layer and optimization techniques in wireless multimedia sensor networks for smart cities.…”

Section: Literature Reviewmentioning

confidence: 99%

The dynamic two-echelon MSW disposal system study under uncertainty in smart city

2021

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The municipal solid waste (MSW) disposal system is the key for building the smart city. In the MSW disposal system, the MSW is allocated among the disposal plants in the first echelon, and then the derivatives (incineration residues and RDF) are allocated between residues disposal plants and markets in the second echelon. In the two-echelon optimal allocation of MSW disposal system, two objectives, cost and environmental impact, should be considered. Considering the uncertainty in the MSW disposal system, this paper constructs a grey fuzzy multi-objective two-echelon MSW allocation model. The model is divided into two sub models and the expected value sorting method is applied to solve the model. The proposed model successfully was applied to a real case in Huangshi, China. The numerical experiments showed RDF technology has advantages on both cost and environmental impact comparing to other disposal technology on disposing MSW.

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Integrated Municipal Solid Waste Management under uncertainty: A tri-echelon city logistics and transportation context

Cited by 44 publications

References 33 publications

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

A novel cooperative model in the collection of infectious waste in COVID-19 pandemic

The dynamic two-echelon MSW disposal system study under uncertainty in smart city

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