A De Novo programming approach for a robust closed-loop supply chain network design under uncertainty: An M/M/1 queueing model

International Journal of Industrial Engineering Computations

Volumn 6, Issue 2, 2015, Pages 211-228

  Saeedi, Sarow ^a   Mohammadi, Mohammad ^a   Torabi, S A ^b  

^a KHARAZMI UNIVERSITY   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Closed loop supply chain (CLSC); De Novo programming; Queueing system; Robust programming; TH method

Indexed keywords

EID: 84921775611     PISSN: 19232926     EISSN: 19232934     Source Type: Journal    
DOI: 10.5267/j.ijiec.2014.11.002     Document Type: Article

References (26)

1. Bazara, M. S., Sherali, H. D., & Shetty, C. M. (2006). Nonlinear programming: theory and algorithms (3rd Ed.). Hoboken, New Jersey: Wiley.
2. Ben-Tal, A., El-Ghaoui, L., & Nemirovski, A. (2009). Robust Optimization. Princeton University Press.
3. Ben-Tal, A., Golany, B., Nemirovski, A., & Vial, J. P. (2005). Retailer-supplier flexible commitments contracts: a robust optimization approach. Manufacturing Services and Operations Management, 7, 248-271.
4. Ben-Tal, A., & Nemirovski, A. (1998). Robust convex optimization. Mathematics of Operation Research, 2, 769-805.
5. Fleischmann, M., Beullens, P., Bloemhof-ruwaard, J. M., & Wassenhove, L. (2001). The impact of product recovery on logistics network design. Production and Operations Management, 10(2), 156-173.
6. Francas, D., & Minner, S. (2009). Manufacturing network configuration in supply chains with product recovery. Omega, 37, 757-769.
7. Georgiadis, P., & Athanasiou, E. (2013). Flexible long-term capacity planning in closed-loop supply chains with remanufacturing. European Journal of Operational Research, 225, 44-58.
8. Georgiadis, P., & Athanasiou, E. (2010). The impact of two-product joint lifecycles on capacity planning of remanufacturing networks. European Journal of Operational Research, 202, 420-433.
9. Kamath, N. B., & Roy, R. (2007). Capacity augmentation of a supply chain for a short lifecycle product: A system dynamics framework. European Journal of Operational Research, 179, 334-351.
10. Ko, H. J., & Evans. G. W. (2007). A genetic-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34, 346-366.
11. Lai, Y. J., & Hwang, C. L. (1993). Possibilistic linear programming for managing interest rate risk. Fuzzy Sets and Systems, 54, 135-146.
12. Lee, D., & Dong, M. (2007). A heuristic approach to logistics network design for end-of-lease computer products recovery. Transportation Research Part E, 44, 455-474.
13. Li, H., Hendry, L., & Teunter, R. (2009). A strategic capacity allocation model for a complex supply chain: Formulation and solution approach comparison. International Journal of Production Economics, 121, 505-518.
14. Li, X. Q., Zhang, B., & Li, B. (2006). Computing efficient solutions to fuzzy multiple objective linear programming problems. Fuzzy Sets and Systems, 157, 1328-1332.
15. Lieckens, K., & Vandaele, N. (2007). Reverse logistics network design with stochastic lead times. Computers & Operations Research, 34, 395-416.
16. Pishvaee, M. S., Farahani, R. Z., & Dullaert, W. (2010). A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers & Operations Research, 37, 1100-1112.
17. Pishvaee, M. S., Jolai, F., & Razmi, J. (2009). A stochastic optimization model for integrated forward/reverse logistics network design. Journal of Manufacturing Systems, 28, 107-114.
18. Pishvaee, M. S., Rabbani, M., & Torabi, S. A. (2011). A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling, 35, 637-649.
19. Salema, M. I. G., Barbosa-Povoa, A. P., & Novais, A. Q. (2007). An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. European Journal of Operational Research, 179, 1063-1077.
20. Selim. H., & Ozkarahan, I. (2008). A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. International Journal of Advanced Manufacturing Technology, 36, 401-418.
21. Soliemani, H., Seyyed-Esfahani, M., & Akbarpour Shirazi, M. (2013). A new multi-criteria scenariobased solution approach for stochastic forward/reverse supply chain network design. Annals of Operations Research, 207(1), 1-23.
22. Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159, 193-214.
23. Vahdani, B., Tavakkoli-Moghaddam, R., & Jolai, F. (2013). Reliable design of a logistics network under uncertainty: A fuzzy possibilistic-queuing model. Applied Mathematical Modelling, 37, 3254-3268.
24. Vlachos, D., Georgiadis, P., & Iakovou, E. (2007). A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains. Computers & Operations Research, 34, 367-394.
25. Zeleny, M. (1981). A case study in multiobjective design: De Novo programming, in: Nijkamp, P., Spronk, J. (Eds.), Multiple Criteria Analysis: Operational methods. Gower Publishing, Hampshire, pp. 37-52.
26. Zeleny, M. (1990). Optimizing given systems vs. designing optimal systems: The De Novo programming approach. General Systems, 17(4), 295-307.