How to cite this paper
Daghigh, R., Jabalameli, M., Amiri, A & Pishvaee, M. (2016). A multi-objective location-inventory model for 3PL providers with sustainable considerations under uncertainty.International Journal of Industrial Engineering Computations , 7(4), 615-634.
Refrences
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Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Transportation Research Part E: Logistics and Transportation Review, 67, 14-38.
Mula, J., Poler, R., & Garcia, J. P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, 157(1), 74-97.
Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34(2), 346-366.
Zhang, Y., Xie, L., Hang, W., & Cui, X. (2007, August). A robust model for 3PLS to design a remanufacturing logistics network under the uncertain environment. In Automation and Logistics, 2007 IEEE International Conference on (pp. 367-372). IEEE.
Mallidis, I., Dekker, R., & Vlachos, D. (2012). The impact of greening on supply chain design and cost: a case for a developing region. Journal of Transport Geography, 22, 118-128.
Ghaffari-Nasab, N., Ghazanfari, M., & Teimoury, E. (2015). Hub-and-spoke logistics network design for third party logistics service providers. International Journal of Management Science and Engineering Management, (ahead-of-print), 1-13.
Dehghanian, F., & Mansour, S. (2009). Designing sustainable recovery network of end-of-life products using genetic algorithm. Resources, Conservation and Recycling, 53(10), 559-570.
Devika, K., Jafarian, A., & Nourbakhsh, V. (2014). Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques. European Journal of Operational Research, 235(3), 594-615.
Ramezani, M., Kimiagari, A. M., Karimi, B., & Hejazi, T. H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems, 59, 108-120.
Torabi, S. A., & Moghaddam, M. (2012). Multi-site integrated production-distribution planning with trans-shipment: a fuzzy goal programming approach. International Journal of Production Research, 50(6), 1726-1748.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Inuiguchi, M., & Ramık, J. (2000). Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy sets and systems, 111(1), 3-28.
Iwamura, K., & Liu, B. (1998). Chance constrained integer programming models for capital budgeting in fuzzy environments. Journal of the Operational Research Society,49(8), 854-860.
Heilpern, S. (1992). The expected value of a fuzzy number. Fuzzy sets and Systems, 47(1), 81-86.
Mavrotas, G. (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), 455-465.
Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214.
Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2014). An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain. Transportation Research Part E: Logistics and Transportation Review, 67, 14-38.
Mula, J., Poler, R., & Garcia, J. P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, 157(1), 74-97.
Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34(2), 346-366.
Zhang, Y., Xie, L., Hang, W., & Cui, X. (2007, August). A robust model for 3PLS to design a remanufacturing logistics network under the uncertain environment. In Automation and Logistics, 2007 IEEE International Conference on (pp. 367-372). IEEE.
Mallidis, I., Dekker, R., & Vlachos, D. (2012). The impact of greening on supply chain design and cost: a case for a developing region. Journal of Transport Geography, 22, 118-128.
Ghaffari-Nasab, N., Ghazanfari, M., & Teimoury, E. (2015). Hub-and-spoke logistics network design for third party logistics service providers. International Journal of Management Science and Engineering Management, (ahead-of-print), 1-13.
Dehghanian, F., & Mansour, S. (2009). Designing sustainable recovery network of end-of-life products using genetic algorithm. Resources, Conservation and Recycling, 53(10), 559-570.
Devika, K., Jafarian, A., & Nourbakhsh, V. (2014). Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques. European Journal of Operational Research, 235(3), 594-615.
Ramezani, M., Kimiagari, A. M., Karimi, B., & Hejazi, T. H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems, 59, 108-120.
Torabi, S. A., & Moghaddam, M. (2012). Multi-site integrated production-distribution planning with trans-shipment: a fuzzy goal programming approach. International Journal of Production Research, 50(6), 1726-1748.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Inuiguchi, M., & Ramık, J. (2000). Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy sets and systems, 111(1), 3-28.
Iwamura, K., & Liu, B. (1998). Chance constrained integer programming models for capital budgeting in fuzzy environments. Journal of the Operational Research Society,49(8), 854-860.
Heilpern, S. (1992). The expected value of a fuzzy number. Fuzzy sets and Systems, 47(1), 81-86.
Mavrotas, G. (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), 455-465.
Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214.