Effects of integrating physical and financial flows through a closed-loop supply chain network under uncertain demand and return

Document Type : Research Paper


School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran


The impact of financial challenges on the profit of a supply chain, have caused the researcher to model the supply chain network by considering the operational and financial dimensions. Also, the establishment of a closed loop supply chain (CLSC) network has a high effect on economic profit. So, the purpose of this study is to design a stochastic closed loop supply chain network by considering the operational and financial dimensions and tactical decision-making level. First, a deterministic mixed-integer linear programming model is developed. Then, the scenario-based of the proposed mixed integer linear programming model is presented. The main innovation of this research is to develop a mathematical model that simultaneously focuses on optimizing the financial and physical flows in an integrated manner and uses the financial ratios in the form of a closed loop supply chain. In order to illustrate the applicability of the proposed model, a test problem from the recent literature is used. The analysis of the results obtained from the developed stochastic mathematical model shows an averagely 4% increase in profit and a 27% reduction in semi-variance compared to deterministic developed models.  


Main Subjects

Altman, E.I., (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, The Journal of Finance, 23, 589–609.
Badell, M.., Fernández, E., GuillénL, G., Puigjaner, L., (2007). Optimal budgets and cash flow during retrofitting period in batch chemical industry, Mathematical and Computer Modelling, 18, 359–372.
Cardoso, S.R., Barbosa-Póvoa, A.P., Relvas, S., (2016). Integrating financial risk measures into the design and planning of closed-loop supply chains, Computers and Chemical Engineering, 85, 105-123.
Chauffour, J.P., Malouche, M., (2011). Trade Finance during the Great Trade Collapse. Washington DC: The World Bank.
Choi, M.J., Lee, S.H., (2011). The multiple traveling purchaser problem for maximizing system’s reliability with budget constraints, Expert Systems with Applications, 38, 9848-9853.
Cui, Y.Y., Guan, Z., Saif, U., Zhang, L., Zhang, F., Mirza, J., (2017). Close Loop Supply Chain Network Problem with Uncertainty in Demand and Returned Products: Genetic Artificial Bee Colony Algorithm Approach, Journal of Cleaner Production, 162, 717-742.
Dal Mas, M, Giarola, S., Zamboni, A., Bezzo, F., (2010). Capacity planning and financial optimization of the bioethanol supply chain underprice uncertainty, in: 20th European Symposium on Computer Aided Process Engineering, Padova, Italy.
Dutta, P., Das, D., Schultmann, F., Fröhling, M., (2016). Design and planning of a closed-loop supply chain with three-way recovery and buyback offer, Journal of Cleaner Production, 135, 604-619.
Elgazzar, S.H., Tipi, N.S., Hubbard, N. J. Leach, D. Z., (2012). Linking supply chain processes’ performance to a company’s financial strategic objectives, The European Journal of Operational Research, 223(1), 276-289.
Feito-Cespon, M., Sarache, W., Piedra-Jimenez, F., Cespon-Castro, R., (2017). Redesign of a sustainable reverse supply chain under uncertainty: A case study, Journal of Cleaner Production, 151, 206-217.
Feng, X., Moon, I., Ryu, K., (2015). Supply chain coordination under budget constraints, Computers & Industrial Engineering, 88, 487–500.
Guillén, G., Badell, M., Puigjaner, L., (2006). A holistic framework for short-term supply chain management integrating production and corporate financial planning, International Journal of Production Economic, 106 (1), 288-306.
Gupta, S., Dutta, K., (2011). Modeling of financial supply chain, European Journal of Operational Research, 211 (1), 47-56.
Hahn, G.J., Kuhn, H., (2012). Simultaneous investment, operations, and financial planning in supply chains: Avalue-based optimization approach, Int. J. Production Economics, 140 (2), 559–569.
Hassanzadeh Amin, S., Zhang, G., Akhtar, P., (2017).  Effects of uncertainty on a tire closed-loop supply chain network, Expert Systems with Applications, 73, 82-91.
Hugo, A., Pistikopoulos, E.N., (2005). Environmentally conscious long-range planning and design of supply chain networks, Journal of Cleaner Production, 13, 1471-1491.
Leung, S.C.H., Tsang, S.O.S., Ng, W.L., Wu, Y., (2007). A robust optimization model for multi-site production planning problem in an uncertain environment, European Journal of Operational Research, 181, 224–238.
Liu, Z., Cruz, J.M., (2012). Supply chain networks with corporate financial risks and trade credits under economic uncertainty, International Journal of Production Economics, 137 (1), 55–67.
Longinidis, P., Georgiadis, M.C., (2011). Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty, International Journal of Production Economics, 129 (2), 262-276.
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.
Melo, M.T., Nickel, S., Gama, F.S., (2005). Dynamic multi commodity capacitated facility location a mathematical modeling framework for strategic supply chain planning, Computers & Operations Research, 33, 181-208.
Mohammadi, A., Abbasi, Abbas., Alimohammadlou, M., Eghtesadifard, M., Khalifeh, M., (2017). Optimal design of a multi-echelon supply chain in a system thinking framework: An integrated financial-operational approach, Computers & Industrial Engineering, 114, 297–315.
Moussawi-Haidar, L., Jaber, M. Y., (2013). A joint model for cash and inventory management for a retailer under delay in payments, Computers & Industrial Engineering, 66 (4), 758-767.
Naderi, M.J., Pishvaee, M.S., (2017). A stochastic programming approach to integrated water supply and wastewater collection network design, Computers and Chemical Engineering, 104, 107–127
Naraharisetti, P.K., Karimi, I.A., Srinivasan, R., (2008). Supply chain redesign through optimal asset management and capital budgeting, Computers and Chemical Engineering, 32 (12), 3153-3169.
Nickel, S., Gama, F.S., Ziegler, H.P., (2012). A multi-stage stochastic supply network design problem with financial decisions and risk management, Omega, 40 (5), 512-524.
Pishvaee, M.S., Fazli Khalaf, M., (2016). Novel robust fuzzy mathematical programming methods, Applied Mathematical Modelling, 40, 407-418.
Pishvaee, M.S., Jolai, F., Razmi, J., (2009). A stochastic optimization model for integrated forward/reverse logistics network design, Journal of Manufacturing Systems, 28, 107-114.
Puigjaner, L., Guillén-Gosálbez, G., (2008). Towards an integrated framework for supply chain management in the batch chemical process industry, Computer & Chemical Engineering, 32 (4), 650-670.
Ramezani, M., Kimiagari, A.M., Karimi, B., (2014). Closed-loop supply chain network design: A financial approach, Applied Mathematical Modelling, 38 (15-16), 4099-4119.
Sodhi, M.M.S., Tang, C.S., (2009). Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset–liability management, International Journal of Production Economics, 121 (2), 728–738.
Vafa Arani, H., Torabi, S.A., (2018). Integrated material-financial supply chain master planning under mixed uncertainty, Information Sciences, 423, 96–114.
Wang, Q., Batta, R., Bhadury, J., Rump, C.M., (2003). Budget constrained location problem with opening and closing of facilities, Computers & Operations Research, 30, 2047-2069.
Xu, X., Cheng, X., Sun, Y., (2015). Coordination contracts for outsourcing supply chain with financial constraint, International Journal of Production Economics, 162, 134-142.