A multi-stage stochastic programming model for sustainable closed-loop supply chain network design with financial decisions: A case study of plastic production and recycling supply chain

This paper proposes a multi-objective, multi-stage programming model to design a sustainable closed-loop supply chain network considering financial decisions. A multi-product, sustainable closed-loop plastic Supply Chain Network Design (SCND) problem, which encompasses economic, environmental, and s...

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Vydáno v:Scientia Iranica. Transaction E, Industrial engineering Ročník 27; číslo 1; s. 377 - 395
Hlavní autoři: Mohammadi, A S, Alemtabriz, A, Pishvaee, M S, Zandieh, M
Médium: Journal Article
Jazyk:angličtina
Vydáno: Tehran Sharif University of Technology 01.01.2020
Témata:
Capital expenditures
Competition
Computer applications
Decision making
Decision making models
Economic models
Integer programming
Landfill
Linear programming
Loans
Multiple objective analysis
Network design
Optimization
Researchers
Return on investment
Stochastic programming
Supply chain management
Supply chains
Sustainability
Sustainable development
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Shrnutí:This paper proposes a multi-objective, multi-stage programming model to design a sustainable closed-loop supply chain network considering financial decisions. A multi-product, sustainable closed-loop plastic Supply Chain Network Design (SCND) problem, which encompasses economic, environmental, and social objectives, is modeled in a mathematical manner. The decisions to be made were concerned with the location of facilities, flow of products, loans to take, and investments to make. Uncertainty issue was about the demand of customers and the rate of return on investment. The decision making model was formulated as a multi-objective, multi-stage mixed-integer linear programming problem and solved by implementing path formulation and augmented econstraint methods. Computational analysis was carried out based on the subject company to determine the significance of the proposed model and the efficiency of integrating financial decisions with SCND decisions.
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DOI:10.24200/sci.2019.21531