Designing Green Closed-loop Supply Chain Network with Financial Decisions under Uncertainty

Document Type : Research Paper


1 Ph.D. Student in Operation Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

2 Prof. of Industrial Management, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran

3 Assistant Prof. of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran


Objective: Effective design of supply chain networks is necessary for micro-economic development. The aim of this study is to design green closed-loop supply chain network with financial decisions considering economic and environmental dimensions of development. Such decisions consist of non-supply chain investments and available loans. Uncertainty of demand and investments related to other investments (ROI) are taken into account, too.
Methods:Proposed model is multi-product, multi-objective, multi-period, stochastic and closed-loop which is modeled as a mixed integer linear programming problem. A scenario path model is applied in order to deal with the uncertainties.
Results: The results approved the effectiveness of considering financial decisions. By increasing the number of available loans, the level of the service delivered to the whole system will increase accompanied by a decreasing inclination. Obtained results are based on a case study in plastic recycling industry.
Conclusion: Simultaneous consideration of financial decisions and uncertainty in supply chain network design can lead to an improvement in the profit of the supply chain.


Aghaei, J., Amjadi, N., & Shayanfar, H.A. (2011). Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method. Applied Soft Computing, 11(4), 3846–3858.
Amin, S. H., & Zhang, G. (2013). A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 37(6), 4165–4176.
Babazadeh, R., Razmi, J., Pishvaee, M. S., & Rabbani, M. (2017). A sustainable second-generation biodiesel supply chain network design problem under risk. Omega (United Kingdom), 66, 258–277.
Bloemhof-Ruwaard, J., Van Wassenhovel, L. N., Gabel, H. L., & Weaver, P. M. (1996). An environmental life cycle optimization model for the European pulp and paper industry. Omega, 6(24), 615–629.
Corsano, G., Vecchietti, A. R., & Montagna, J. M. (2011). Optimal design for sustainable bioethanol supply chain considering detailed plant performance model. Computers and Chemical Engineering, 35(8, S1), 1384–1398.
Costi, P., Minciardi, R., Robba, M., Rovatti, M., & Sacile, R. (2004). An environmentally sustainable decision model for urban solid waste management. Waste Management, 24(3), 277–295.
Ebrahimi, M., Safari, H., & Sadeghi-Moghadam, M. R. (2018). A Supply chain continuity model based on axiomatic design approach. Industrial Management Journal, 9(4), 563-586. (in Persian)
Fallah-Lajimi, H. R., Arab, A., & Bahramzadeh, H. (2017). Investigate the barriers of implement green supply chain in Mazandaran steel industry with a combined approach BSC / BWM. Industrial Management Journal, 8(4), 653-684. (in Persian)
Grossmann, I. E., & Guillén-Gosálbez, G. (2010). Scope for the application of mathematical programming techniques in the synthesis and planning of sustainable processes. Computers & Chemical Engineering, 34(9), 1365–1376.
Giarola, S., Shah, N., & Bezzo, F. (2012). A comprehensive approach to the design of ethanol supply chains including carbon trading effects. Bioresource Technology, 107, 175–185.
Golpira, H., Zandieh, M., Najaa, E., & Sadi-Nezhad, S. (2017). A multi-objective, multi-echelon green supply chain network design problem with risk-averse retailers in an uncertain environment. Scientia Iranica E, 24(1), 413–423.
Guillén-Gosálbez, G., & Grossmann, I. (2010). A global optimization strategy for the environmentally conscious design of chemical supply chains under uncertainty in the damage assessment model. Computers & Chemical Engineering, 34(1), 42–58.
Guillén-Gosálbez, G., & Grossmann, I. (2009). Optimal design and planning of sustainable chemical supply chains under uncertainty. AICHE journal, 55(1), 99–121.
Guillen, G., Badell, M., & Puigjaner, L. (2007). A holistic framework for short-term supply chain management integrating production and corporate financial planning. International Journal of Production Economics, 106(1), 288–306.
Kalantari, M., Pishvaee, M. S., & Yaghoubi, S. (2015). A multi-objective optimization model for integrating financial and phisical flow in supply chain master planning. Journal of Industrial Management Perspective, 19, 9-31. (in Persian)
Laı, J.M., Guille, G., Badell, M., Espun, A., & Puigjaner, L. (2007). Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains. Industrial and Engineering Chemistry Research, 46(23), 7739–7757.
Lira-Barragán, L. F., Ponce-Ortega, J. M., Serna-González, M., & El-Halwagi, M. (2011). An MINLP Model for the Optimal Location of a New Industrial Plant with Simultaneous Consideration of Economic and Environmental Criteria. Industrial Engineering Chemistry Research, 50(2), 953–964.
Longinidis, P., & Georgiadis, M. C. (2013). Managing the trade-offs between financial performance and credit solvency in the optimal design of supply chain networks under economic uncertainty. Computers and Chemical Engineering, 48, 264–279.
MA, R., YAO, L., JIN, M., REN, P., & LV, Z. (2016). Robust environmental closed-loop supply chain design under uncertainty. Chaos, Solitons and Fractals, 89, 195–202.
Mavrotas, G. (2009). Effective implementation of the ??-constraint method in Multi-Objective Mathematical Programming problems. Applied Mathematics and Computation, 213(2), 455–465.
Moazzez, H., & Azizi, J. (2016). Developing the green supply chain management model of Yang in Cinere company. Industrial Management Journal, 8(2), 309-332. (in Persian)
Mohammadi, M., Torabi, S. a., & Tavakkoli-Moghaddam, R. (2014). Sustainable hub location under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review, 62, 89–115.
Mohammed, F., Selim, S. Z., Hassan, A., & Syed, M. N. (2017). Multi-period planning of closed-loop supply chain with carbon policies under uncertainty. Transportation Research Part D: Transport and Environment, 51, 146–172.
Mohseni, S., & Pishvaee, M. S. (2016). A robust programming approach towards design and optimization of microalgae-based biofuel supply chain. Computers & Industrial Engineering, 100, 58-71.
Nickel, S., Saldanha-da-Gama, F., & Ziegler, H.-P. (2012). A multi-stage stochastic supply network design problem with financial decisions and risk management. Omega, 40(5), 511–524.
Pishvaee, M. S., & Razmi, J. (2012). Environmental supply chain network design using multi-objective fuzzy mathematical programming. Applied Mathematical Modelling, 36(8), 3433–3446.
Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy Sets and Systems, 206, 1–20.
Pishvaee, M. S., Torabi, S. A., & Razmi, J. (2012). Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty. Computers & Industrial Engineering, 62(2), 624–632.
Pishvaee, M. S., Zanjirani Farahani, R., & Dullaert, W. (2006). C A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers & Operations Research, 37(6), 1100–1112.
PlasticsEurope. (2016). Plastic - the facts 2016, 38. Retrieved from http://www.plasticseurope. es/Document/plastics---the-facts-2016-15787.aspx?FolID=2.
Ruiz-Femenia, R., Guillen-Gosalbez, G., Jimenez, L., & Caballero, J. a. (2013). Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty. Chemical Engineering Science, 95, 1–11.
Saffar, M. M., G, H. S., & Razmi, J. (2015). A new multi objective optimization model for designing a green supply chain network under uncertainty. International Journal of Industrial Engineering Computations, 6, 15–32.
Saffar, M. M., Shakouri G., H., & Razmi, J. (2014). A new bi-objective mixed integer linear programming for designing a supply chain considering CO2 emission. Uncertain Supply Chain Management, 2(4), 275–292.
Shapiro, J. F. (2004). Challenges of strategic supply chain planning and modeling.. Computers & Chemical Engineering, 28(6), 855–861.
Soleimani, H., Govindan, K., Saghafi, H., & Jafari, H. (2017). Fuzzy Multi-Objective Sustainable and Green Closed-Loop Supply Chain Network Design. Computers & Industrial Engineering, 109, 191-203.
Srivastava, S. K. (2007). Green supply‐chain management: a state‐of‐the‐art literature review. International Journal of Management Reviews, 9(1), 53–80.
Stadtler, H., & Kilger, C. (2005). Supply chain management and advance planning (3rd ed.). Springer.
Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill, USA.
Verma, M., Gendreau, M., & Laporte, G. (2013). Optimal location and capability of oil-spill response facilities for the south coast of Newfoundland. Omega, 41(5), 856–867.
Yilmaz Balaman, Ş., & Selim, H. (2016). Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach. Journal of Cleaner Production, 133, 863-885.