Designing an integrated municipal solid waste management system using a fuzzy chance-constrained programming model considering economic and environmental aspects under uncertainty

•A novel MILP model for designing an efficient waste management system,•Economic and environmental aspects evaluation under uncertain conditions,•Fuzzy weighted goal programming (WGP) approach implementation on the model,•Real case study investigation along with sensitivity analyses. In recent decad...

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Vydáno v:Waste management (Elmsford) Ročník 125; s. 268 - 279
Hlavní autoři: Bavaghar Zaeimi, Mehdi, Abbas Rassafi, Amir
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier Ltd 15.04.2021
Témata:
case studies
computer software
Fuzzy chance-constrained programming model
Humans
Iran
Location-allocation
management systems
model validation
municipal solid waste
Municipal solid waste management
Pollutant emissions
pollutants
Recycling
Refuse Disposal
Solid Waste
transportation
Transportation planning
Uncertainty
Waste Management
Iran
Pollutant emissions
Location-allocation
Municipal solid waste management
Transportation planning
Fuzzy chance-constrained programming model
ISSN:0956-053X, 1879-2456, 1879-2456
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Shrnutí:•A novel MILP model for designing an efficient waste management system,•Economic and environmental aspects evaluation under uncertain conditions,•Fuzzy weighted goal programming (WGP) approach implementation on the model,•Real case study investigation along with sensitivity analyses. In recent decades, municipal solid waste (MSW) management has become one of the major concerns of human societies. Therefore, an efficient MSW system of collecting, recycling, and disposing is required to be designed, maintained and improved continuously. However, designing a proper waste collection management system by controlling the spread of diseases and environmental pollutants is very costly. To provide an efficient MSW management system, this study proposes an integrated location-allocation problem to plan the operations such as collection, recycling, disposal, and transportation under uncertainty. To deal with the problem uncertainty, a triangular fuzzy number approach is employed and finally, a fuzzy chance-constrained programming model is developed. Moreover, the proposed bi-objective mathematical programming model aims to minimize the total costs and the total volume of pollutant emissions simultaneously. To solve and validate the model, a weighted goal programming (WGP) method is employed and solved by CPLEX solver of GAMS software. Finally, a real case study problem was implemented in Qazvin, Iran. The results showed that, in most cases, increasing the confidence level of the case study problem leads to the improvement of objective functions. Managers can take into account the output of this research provided along with a sensitivity analysis under different conditions.
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ISSN:0956-053X
1879-2456
1879-2456
DOI:10.1016/j.wasman.2021.02.047