[1] Pishvaee, M.S., Torabi, S.A., “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”, Fuzzy Sets and Systems, No. 161, pp. 2668–2683, 2010.
[2] Pishvaee, M. S., Torabi, S.A. and Razmi, J,. “Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty”, Computers & Industrial Engineering, No. 62, pp. 624–632, 2012
[3] Kabak, Ö., andÜlengin, F., "Possibilistic linear-programming approach for supply chain networking decisions," European Journal of Operational Research, vol. 209, pp. 253-264, 2011.
[4] Qin, Z., andJi, X., "Logistics network design for product recovery in fuzzy environment," European Journal of Operational Research, vol. 202, pp. 479-490, 2010.
[5] Baykasoǧlu, A., andGöçken, T., "A review and classification of fuzzy mathematical programs," Journal of Intelligent and Fuzzy Systems, vol. 19, pp. 205-229, 2008.
[6] Baykasoǧlu, A., andGöçken, T., "A direct solution approach to fuzzy mathematical programs with fuzzy decision variables," Expert Systems with Applications, vol. 39, pp. 1972-1978, 2012.
[7] Tanaka, H., andAsai, K., "Fuzzy linear programming problems with fuzzy numbers," Fuzzy Sets and Systems, vol. 13, pp. 1-10, 1984.
[8] Tanaka, H., Guo, P., and Zimmermann, H. J., "Possibility distributions of fuzzy decision variables obtained from possibilistic linear programming problems," Fuzzy Sets and Systems, vol. 113, pp. 323-332, 2000.
[9] Allahviranloo, T., HosseinzadehLotfi, F., Kiasary, M. K., Kiani, N. A., and Alizadeh, L., "Solving fully fuzzy linear programming problem by the ranking function," Applied Mathematical Sciences, vol. 2, pp. 19-32, 2008.
[10] Hashemi, S. M., Modarres, M., Nasrabadi, E., and Nasrabadi, M. M., "Fully fuzzified linear programming, solution and duality," Journal of Intelligent and Fuzzy Systems, vol. 17, pp. 253-261, 2006.
[11] Tapkan, P., ÖZbakıR, L., and Baykasoğlu, A., "Solving fuzzy multiple objective generalized assignment problems directly via bees algorithm and fuzzy ranking," Expert Systems with Applications, vol. 40, pp. 892-898, 2013.
[12] Kumar, A., Kaur, J., and Singh, P., "A new method for solving fully fuzzy linear programming problems," Applied Mathematical Modelling, vol. 35, pp. 817-823, 2011.
[13] Fazlollahtabar, H., Mahdavi, I., and Mohajeri, A., "Applying fuzzy mathematical programming approach to optimize a multiple supply network in uncertain condition with comparative analysis," Applied Soft Computing, pp. 550–562, 2012.
[14] Jiménez, M., "Ranking fuzzy numbers through the comparison of its expected intervals," International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 4, pp. 379-388, 1996.
[15] Chen L. H., and Lu, H. W., "An approximate approach for ranking fuzzy numbers based on left and right dominance," Computers and Mathematics with Applications, vol. 41, pp. 1580–1602, 2001.
[16] Torabi S., andHassini, E., "An interactive possibilistic programming approach for multiple objective supply chain master planning," Fuzzy Sets and Systems, vol. 159, pp. 193-214, 2008.
[17] Altiparmak, F., Gen, M., Lin, L., and Karaoglan, I., "A steady-state genetic algorithm for multi-product supply chain network design," Computers & Industrial Engineering, vol. 56, pp. 521-537, 2009.
[18] Wang, H.-F., and Hsu, H.-W., "A closed-loop logistic model with a spanning-tree based genetic algorithm," Computers & Operations Research, vol. 37, pp. 376-389, 2010.