A New Combination of Robust-possibilistic Mathematical Programming for Resilient Supply Chain Network under Disruptions and Uncertainty: A Real Supply Chain (RESEARCH NOTE)


Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran


Nowadays, the design of a strategic supply chain network under disruption is one of the most important priorities of the governments. One of the strategic purposes of managers is to supply the sustainable agricultural products and food in stable conditions which require the production of soil nutrients. In this regard, some disruptions such as sanctions and natural disasters have a destructive effect on the supply of raw materials and the uncertainty of input parameters plays an undesirable impact on the decision-making levels including strategic, tactical, and operational levels. The present study introduced a new model of resilient supply chain network which was compatible with the realities of the structure of the supply chain for fertilizer in Iran. Notably, the effectiveness of the designed system was promoted by the dominant strategies of reliability. Further, a new robust possibilistic approach was proposed which guaranteed the optimality and feasibility robustness through the efficient solution to deal with the parametric uncertainty. Finally, the results showed that the proposed new robust possibilistic combination promoted the optimality robustness and its effectiveness using an optimal average cost and minimum standard deviation.


1.     de Sousa, R.T.X., Korndörfer, G.H., Brem Soares, R.A. and Fontoura, P.R., "Phosphate fertilizers for sugarcane used at pre-planting (phosphorus fertilizer application)", Journal of Plant Nutrition,  Vol. 38, No. 9, (2015), 1444-1455.
2.     Ghomi-Avili, M., Tavakkoli-Moghaddam, R., Jalali, G. and Jabbarzadeh, A., "A network design model for a resilient closed-loop supply chain with lateral transshipment", International Journal of Engineering-Transactions C: Aspects,  Vol. 30, No. 3, (2017), 374.
3.     Üster, H. and Hwang, S.O., "Closed-loop supply chain network design under demand and return uncertainty", Transportation Science,  Vol. 51, No. 4, (2016), 1063-1085.
4.     Vahdani, B., Tavakkoli-Moghaddam, R., Jolai, F. and Baboli, A., "Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model", Engineering Optimization,  Vol. 45, No. 6, (2013), 745-765.
5.     Golpîra, H., Najafi, E., Zandieh, M. and Sadi-Nezhad, S., "Robust bi-level optimization for green opportunistic supply chain network design problem against uncertainty and environmental risk", Computers & Industrial Engineering,  Vol. 107, (2017), 301-312.
6.     Snyder, L.V. and Daskin, M.S., "Stochastic p-robust location problems", IIE Transactions,  Vol. 38, No. 11, (2006), 971-985.
7.     Pan, F. and Nagi, R., "Robust supply chain design under uncertain demand in agile manufacturing", Computers & Operations Research,  Vol. 37, No. 4, (2010), 668-683.
8.     Pishvaee, M.S., Razmi, J. and Torabi, S.A., "Robust possibilistic programming for socially responsible supply chain network design: A new approach", Fuzzy Sets and Systems,  Vol. 206, No., (2012), 1-20.
9.     Hatefi, S. and Jolai, F., "Robust and reliable forward–reverse logistics network design under demand uncertainty and facility disruptions", Applied Mathematical Modelling,  Vol. 38, No. 9-10, (2014), 2630-2647.
10.   Zhang, P. and Zhang, W.-G., "Multiperiod mean absolute deviation fuzzy portfolio selection model with risk control and cardinality constraints", Fuzzy sets and systems,  Vol. 255, No., (2014), 74-91.
11.   Hamidieh, A., Naderi, B., Mohammadi, M. and Fazli-Khalaf, M., "A robust possibilistic programming model for a responsive closed loop supply chain network design", Cogent Mathematics & Statistics,  Vol. 4, No. 1, (2017), 1329886.
12.   Farrokh, M., Azar, A., Jandaghi, G. and Ahmadi, E., "A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty", Fuzzy Sets and Systems,  (2017).
13.   Fazli-Khalaf, M. and Hamidieh, A., "A robust reliable forward-reverse supply chain network design model under parameter and disruption uncertainties", International Journal of Engineering-Transactions B: Applications,  Vol. 30, No. 8, (2017), 1160.
14.   Azad, N., Saharidis, G.K., Davoudpour, H., Malekly, H. and Yektamaram, S.A., "Strategies for protecting supply chain networks against facility and transportation disruptions: An improved benders decomposition approach", Annals of Operations Research,  Vol. 210, No. 1, (2013), 125-163.
15.   Jabbarzadeh, A., Jalali Naini, S.G., Davoudpour, H. and Azad, N., "Designing a supply chain network under the risk of disruptions", Mathematical Problems in Engineering,  Vol. 2012, No., (2012).
16.   Namdar, J., Tavakkoli-Moghaddam, R., Sahebjamnia, N. and Soufi, H.R., "Designing a reliable distribution network with facility fortification and transshipment under partial and complete disruptions", International Journal of Engineering-Transactions C: Aspects,  Vol. 29, No. 9, (2016), 1273.
17.   Carvalho, H., Azevedo, S.G. and Cruz-Machado, V., "Agile and resilient approaches to supply chain management: Influence on performance and competitiveness", Logistics research,  Vol. 4, No. 1-2, (2012), 49-62.
18.   Jüttner, U. and Maklan, S., "Supply chain resilience in the global financial crisis: An empirical study", Supply Chain Management: An International Journal,  Vol. 16, No. 4, (2011), 246-259.
19.   Mari, S.I., Lee, Y.H. and Memon, M.S., "Sustainable and resilient supply chain network design under disruption risks", Sustainability,  Vol. 6, No. 10, (2014), 6666-6686.
20.   Carvalho, H., Azevedo, S.G. and Cruz-Machado, V., "An innovative agile and resilient index for the automotive supply chain", International Journal of Agile Systems and Management,  Vol. 6, No. 3, (2013), 259-283.
21.   Klibi, W. and Martel, A., "Modeling approaches for the design of resilient supply networks under disruptions", International Journal of Production Economics,  Vol. 135, No. 2, (2012), 882-898.
22.   Sawik, T., "Selection of resilient supply portfolio under disruption risks", Omega,  Vol. 41, No. 2, (2013), 259-269.
23.   Hasani, A. and Khosrojerdi, A., "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study", Transportation Research Part E: Logistics and Transportation Review,  Vol. 87, No., (2016), 20-52.
24.   Jiménez, M., Arenas, M., Bilbao, A. and Rodrı, M.V., "Linear programming with fuzzy parameters: An interactive method resolution", European Journal of Operational Research,  Vol. 177, No. 3, (2007), 1599-1609.
25.   Pishvaee, M.S. and Torabi, S.A., "A possibilistic programming approach for closed-loop supply chain network design under uncertainty", Fuzzy sets and systems,  Vol. 161, No. 20, (2010), 2668-2683.
26.   Pishvaee, M.S. and Khalaf, M.F., "Novel robust fuzzy mathematical programming methods", Applied Mathematical Modelling,  Vol. 40, No. 1, (2016), 407-418.
27.   Mousazadeh, M., Torabi, S.A. and Zahiri, B., "A robust possibilistic programming approach for pharmaceutical supply chain network design", Computers & Chemical Engineering,  Vol. 82, No., (2015), 115-128.