Altiparmak, F., Gen, M., Lin, L., & Karaoglan, I. (2009). A steady-state genetic algorithm for multi-product supply chain network design. Computers & Industrial Engineering, 56, 521–537.
Altiparmak, F., Gen, M., Lin, L., & Paksoy, T. (2006). A genetic algorithm for multi-objective optimization of supply chain networks. Computers & Industrial Engineering, 51, 197–216.
Barros, A. I., Dekker, R., & Scholten, V. (1998). A two-level network for recycling sand: a case study. European Journal of Operational Research, 110, 199–214.
Charnes, A., & Cooper W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York.
Du, F., & Evans, G. W. (2008). A bi-objective reverse logistics network analysis for post-sale service.
Computers and Operations Research, 35, 2617 – 2634.
Gen, M., Altiparmak, F., & Lin, L. (2006). A genetic algorithm for two-stage transportation problem using priority-based encoding. OR Spectrum, 28, 337–354.
Gen, M., & Cheng, R. (2000). Genetic algorithms and engineering optimization. John Wiley and Sons, New York.
Gen, M., & Syarif, A. (2005). Hybrid genetic algorithm for multi-time period production/distribution planning. Computers & Industrial Engineering, 48, 799–809.
Huang, X. (2006). Optimal project selection with random fuzzy parameters, International Journal of Production Economics, 112-122.
Jaramillo, J. H., Bhadury J, & Batta, R. (2002). On the use of genetic algorithms to solve location problems. Computers and Operations Research, 29, 761-779.
Jayaraman, V., Guide, V. D., & Srivastava, R. (1999). A closed loop logistics model for remanufacturing. Journal of the Operational Research Society, 50, 497–508.
Jayaraman, V., Patterson, R. A., & Rolland, E. (2003). The design of reverse distribution networks: Models and solution procedures. European Journal of Operational Research, 150, 128–149.
Kara, S., Rugrungruang, F., & Kaebernick, H. (2007). Simulation modeling of reverse logistics networks. International Journal of Production Economics,106, 61–69. Kim, K., Song, I., Kim, J., & Jeong, B. (2006). Supply planning model for remanufacturing system in reverse
logistics environment. Computers & Industrial Engineering, 51, 279–287.
Kirkke, H. R., Harten, A. V., & Schuur, P. C. (1999). Business case Oce: reverse logistic network redesign for
copiers. OR Spectrum, 21,381–409.
Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers and Operations Research, 34, 346–366.
Kwakernaak, H. (1978). random variables: Definitions and theorems. 15, 1-29.
Lee, D.H., & Dong, M. (2008). A heuristic approach to logistics network design for end-of-lease computer products recovery. Transportation Research Part E , 44, 455-474.
Lee, J. E., Gen, M., & Rhee, K. G. (2009). Network model and optimization of reverse logistics by hybrid genetic algorithm. Computers & Industrial Engineering, 56, 951–964.
Liu, B. (2001). Fuzzy random chance-constrained programming, IEEE Transactions on Fuzzy Systems, 9(5),
713-720.
Liu, B. (2002a). Random fuzzy dependent-chance programming and its hybrid intelligent algorithm, Information Sciences, 141 (3–4), 259–271.
Liu, B. (2002b). Theory and Practice of Uncertain Programming, Physica-Verlag, Heidelberg.
Liu, B. (2006). Theory and Practice of Uncertain Programming. Beijing, China: Uncertainty Theory Laboratory- Department of Mathematical Sciences-Tsinghua University.
Liu, B. (2009). Theory and Practice of Uncertain Programming (3rd ed.). Beijing, China: Uncertainty Theory Laboratory- Department of Mathematical Sciences-Tsinghua University.
Liu, B., Iwamura, K. (1998). Chance constrained programming with fuzzy parameters, Fuzzy Sets and Systems, 94, 227–237.
Liu, Y., & Liu, B. (2003). A class of fuzzy random optimization: Expected value models. Information Sciences, 155, 89-102.
Liu, Y., & Liu, B. (2003). Expected value operator of random fuzzy variable and random fuzzy expected value
models, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11 (2), 195–215.
Lu, Z., & Bostel, N. (2007). A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Computers and Operations Research, 34: 299–323.
Michalewicz, Z., Vignaux, G. A., & Hobbs, M. (1991). A non-standard genetic algorithm for the nonlinear transportation problem. ORSA Journal on Computing, 3, 307–316.
Min, H., Ko, H. J., & Ko, C. S. (2006). A genetic algorithm approach to developing the multi-echelon reverse
logistics network for product returns. Omega, 34, 56 – 69.
Min, H., Ko, H. J., & Park, B. I. (2005). A Lagrangian relaxation heuristic for solving the multi-echelon, multicommodity,
closed-loop supply chain network design problem. International Journal of Logistics Systems
and Management, 1, 382–404.
Pishvaee, M. S., Jolai, F., & Razmi, J. (2009). A stochastic optimization model for integrated forward/reverse logistics A stochastic optimization model for integrated forward/reverse logistics. Journal of Manufacturing Systems , 107-114.
Pishvaee, M. S., Zanjirani Farahani, R., & Dullaert, W. (2010). A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers & Operations Research, 37, 1100-1112.
Shen, Z.M. (2007). Integrated supply chain design models: a survey and future research directions. Journal of Industrial and Management Optimization, 3(1),1-27.
Syarif, A., Yun, Y. S., & Gen, M. (2002). Study on multi-stage logistic chain network: a spanning tree-based
genetic algorithm approach. Computers & Industrial Engineering, 43, 299-314.
Wen, M., & Iwamura, K. (2008). Facility location–allocation problem in random fuzzy environment: Using (?,B)-cost minimization model under the Hurewicz criterion. Computers & Mathematics with Applications,
55(4), 704-713.
Xu, J., Liu, Q., & Wang, R. (2008). A class of multi-objective supply chain networks optimal model under random fuzzy environment and its application to the industry of Chinese liquor. Information Sciences, 178, 2022–2043.