Al-e-hashem, S., Malekly, H., & Aryanezhad, M. (2011). A multi-objective robust optimization
model for multi-product multi-site aggregate production planning in a supply chain under
uncertainty. International Journal of Production Economics, 134, 28-42.
http://dx.doi.org/10.1016/j.ijpe.2011.01.027
Altiparmak, F., Gen, M., Lin, L., & Paksoy, T. (2006). A genetic algorithm approach for multiobjective
optimization of supply chain networks. Computers & Industrial Engineering, 51(1),
196-215. http://dx.doi.org/10.1016/j.cie.2006.07.011
Arikan, F. (2013). A fuzzy solution approach for multi objective supplier selection. Expert
Systems with Applications, 40(3), 947-952. http://dx.doi.org/10.1016/j.eswa.2012.05.051
Chen, C., & Lee, W. (2004). Multi-objective optimization of multi-echelon supply chain
networks with uncertain product demands and prices. Computers & Chemical Engineering,
28(6-7), 1131-1144. http://dx.doi.org/10.1016/j.compchemeng.2003.09.014
Coello, C., & Lechuga, M. (2002). MOPSO: A proposal for multiple objective particle swarm
optimization. In Proceedings of the 2002 Congress on Evolutionary Computation, 1051-1056.
Dubois, D., & Prade, H. (1988). Possibility Theory: An Approach to Computerized Processing of
Uncertainty. New York: Plenum. http://dx.doi.org/10.1007/978-1-4684-5287-7
Garg, H., & Sharma, S. (2013). Multi-objective reliability-redundancy allocation problem using
particle swarm optimization. Computers & Industrial Engineering, 64(1), 247-255.
http://dx.doi.org/10.1016/j.cie.2012.09.015
Giannoccaro, I., Pontrandolfo, P., & Scozzi, B. (2003). A fuzzy echelon approach for inventory
management in supply chains. European Journal of Operational Research, 149(1), 185-196.
http://dx.doi.org/10.1016/S0377-2217(02)00441-1
Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In Proceedings of the IEEE
Conference on Neural Networks, 1942-1948. Piscataway: IEEE Service Center.
Kennedy, J., & Eberhart, R. (2001). Swarm Intelligence. Morgan Kaufmann.
Knowles, J., & Corne, D. (2000). Approximating the nondominated front using the pareto
archived evolution strategy. Evolution Computation, 8, 149-172.
http://dx.doi.org/10.1023/A:1013771608623
Liu, B. (2002). Toward fuzzy optimization without mathematical ambiguity. Fuzzy Optimization
and Decision Making, 1(1), 43-63. http://dx.doi.org/10.1023/A:1013771608623
Liu, Y., & Xu, J. (2006). A class of bifuzzy model and its application to single-period inventory
problem. World Journal of Modelling and Simulation, 2(2), 109-118.
Luhandjula, M. (1987). Multiple objective programming problems with possibility coefficients.
Fuzzy Sets and Systems, 21, 135-145. http://dx.doi.org/10.1016/0165-0114(87)90159-X
Nahmias, S. (1978). Fuzzy variables, Fuzzy Sets and Systems, 1, 97-110.
http://dx.doi.org/10.1016/0165-0114(78)90011-8
Shi, Y., & Eberhart, R. (1998). Particle swarm optimization. In Proc. IEEE Int. Conf. on Neural
Networks, 69-73.
Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2000). Designing and Managing the Supply
Chain. New York: Irwin McGraw-Hill.
Tabrizi, B., & Razmi, J. (2013). Introducing a mixed-integer non-linear fuzzy model for risk
management in designing supply chain networks, Journal of Manufacturing Systems, 32(2),
295-307. http://dx.doi.org/10.1016/j.jmsy.2012.12.001
Tavakkoli-Moghaddam, R., Azarkish, M., & Sadeghnejad-Barkousaraie A. (2011). A new hybrid
multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem.
Expert Systems with Applications, 38(9), 10812-10821. http://dx.doi.org/10.1016/j.eswa.2011.02.050
Torabi, S., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple
objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214.
http://dx.doi.org/10.1016/j.fss.2007.08.010
Wang, J., & Shu, Y. (2008). Fuzzy decision modeling for supply chain management. Fuzzy Sets
and Systems, 150(1), 107-127. http://dx.doi.org/10.1016/j.fss.2004.07.005
Wei, C., Liang, G., & Wang, M. (2007). A comprehensive supply chain management project
selection framework under fuzzy environment. International Journal of Project Management,
25(6), 627-636. http://dx.doi.org/10.1016/j.ijproman.2007.01.010
Xu, J., & Liu, Y. (2008). Multi-objective decision making model under fuzzy random
environment and its application to inventory problems. Information Sciences, 178,
2899-2914. http://dx.doi.org/10.1016/j.ins.2008.03.003
Xu, J., & Yan, F. (2011). A multi-objective decision making model for the vendor selection
problem in a bifuzzy environment. Expert Systems with Applications, 38(8), 9684-9695.
http://dx.doi.org/10.1016/j.eswa.2011.01.168
Xu, J., & Zhou, X. (2011). Fuzzy-Like Multiple Objective Decision Making. Berlin Heidelberg:
Springer-Verlag.
Yan, L. (2009). Risk Curve and Bifuzzy Portfolio Selection. Journal of Mathematics Research,
1(2), 193-198. http://dx.doi.org/10.5539/jmr.v1n2p193
Zadeh. L. (1965). Fuzzy sets. Information and Control, 8, 338-353.
http://dx.doi.org/10.1016/S0019-9958(65)90241-X
Zadeh. L. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1,
3-28. http://dx.doi.org/10.1016/0165-0114(78)90029-5
Zhang, G., Shao, X., Li, P., & Gao, L. (2009). An effective hybrid particle swarm optimization
algorithm for multi-objective flexible job-shop scheduling problem. Computers & Industrial
Engineering, 56(4), 1309-1318. http://dx.doi.org/10.1016/j.cie.2008.07.021
Thank you for copying data from http://www.arastirmax.com