Alireza Abbaszadeh Molaei; Abdollah Arasteh; Mir Saman Pishvaee
Abstract
In today’s growing world, the Green Supply Chain (GSC) is a new approach to include environmental impacts and economic goals in a supply chain network. This paper continues previous research studies by designing a new green supply chain network considering different social, economic, environmental, ...
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In today’s growing world, the Green Supply Chain (GSC) is a new approach to include environmental impacts and economic goals in a supply chain network. This paper continues previous research studies by designing a new green supply chain network considering different social, economic, environmental, service level, and shortage aspects. This study introduces a fresh, comprehensive tradeoff model that considers factors such as overall expenses, quality of service, environmental pollution levels, and societal impacts within a sustainable supply chain. The proposed model is formulated as a multi-product multi-objective mixed-integer programming model to assist in planning a green supply chain. The suggested model has three objective functions: maximizing social responsibility, minimizing the cost of carbon dioxide (CO2) emissions, and minimizing economic costs. The model allows for shortages in the form of backorders and seeks to maximize service level in addition to the mentioned objective functions. Robust Possibilistic Programming (RPP) was employed to deal with the problem's uncertain input parameters in the solution approach. Also, a multi-objective model of the problem was solved using Fuzzy Goal Programming (FGP). To examine and evaluate the model in a simple framework, the proposed mathematical model of the problem was implemented in an industrial unit in the real world, and the results obtained from it were analyzed. Among the results that the output of the model provides to managers and decision-makers, it is possible to mention the determination of the optimal amount of production of each product in the manufacturing plants, quantity of products and parts transported between facilities, and also the determination of the of network's carbon emissions which is equal to 51.59 tons.
Fatemeh Amirbeygi; Seyyed Hosein Seyyed Esfahani; Behrooz Khorshidvand
Abstract
Environmental pollution and the deterioration of natural resources are now considered significant challenges in human societies. In fact, environmental pollution is mainly caused by manufacturing industries. Most industries (e.g., the cement industry) employ the green supply chain to overcome ecological ...
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Environmental pollution and the deterioration of natural resources are now considered significant challenges in human societies. In fact, environmental pollution is mainly caused by manufacturing industries. Most industries (e.g., the cement industry) employ the green supply chain to overcome ecological problems, a goal that requires various techniques for quantifying the environmental impacts on the supply chain to improve processes. This study aimed to evaluate the green supply chain performance at 11 cement manufacturing factories through the hybrid BSC–DEA approach within the 2018–2020 period. After the principal indices were identified and placed in each perspective of the balanced scorecard (BSC), the DEMATEL technique was adopted to determine the relationships of perspectives. The multistage data envelopment analysis (DEA) model was then employed to measure the efficiency of each BSC perspective and the total network efficiency. Finally, reference units were introduced to improve the inefficient units. According to the results, managers focus mainly on the financial section and customers but pay less attention to growth and learning. The organization yielded the best efficiency in 2020 by following an upward trend. The energy consumption rate, clinker–cement ratio, and CO2 emission rate were analyzed in this study to better investigate the environmental problems in the cement industry. Most of the units followed upward trends in both CO2 emission and energy consumption but experienced a downward trend in clinker production.
H. Golpira; M. Zandieh; E. Najafi; S. Sadi Nezhade
Volume 2, Issue 2 , December 2015, , Pages 43-54
Abstract
Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model ...
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Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model considers minimization of supply chain costs while the second objective function minimizes CO2 emission level. The Conditional Value at Risk (CVaR) approach is used to deal with the demand uncertainty in supply chain network in addition to the scenario based approach that is employed to deal with the stochastic level of CO2 emission. The implementation of the proposed model has been demonstrated using some randomly selected numbers and the results are analyzed accordingly.