Reverse channel decisions for a fuzzy closed-loop supply chain

Applied Mathematical Modelling

Volumn 37, Issue 3, 2013, Pages 1502-1513

  Wei, Jie ^a   Zhao, Jing ^b  

^a MILITARY TRANSPORTATION UNIVERSITY   (China)

^b TIANJIN POLYTECHNIC UNIVERSITY   (China)

Author keywords

Closed loop supply chain; Fuzzy theory; Game theory; Reverse channel decisions

Indexed keywords

CLOSED-LOOP SUPPLY CHAIN; EXPECTED VALUE MODEL; FUZZY THEORY; NEW PRODUCT; OPTIMAL STRATEGIES; REVERSE CHANNELS; THIRD PARTIES; USED PRODUCT;

GAME THEORY; MANUFACTURE; PROFITABILITY; SALES;

LINEAR MATRIX INEQUALITIES;

EID: 84870253772     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2012.04.003     Document Type: Article

References (33)

1. Prahinski C., Kocabasoglu C. Empirical research opportunities in reverse supply chains. Omega 2006, 34:519-532.
2. Savaskan R.C., Bhattacharya S., Wassenhove L.N.V. Closed-loop supply chain models with product remanufacturing. Manage. Sci. 2004, 50:239-252.
3. Kim K., Song I., Kim J., Jeong B. Supply planning model for remanufacturing system in reverse logistics environment. Comput. Ind. Eng. 2006, 51:279-287.
4. Dowlatshahi S. A strategic framework for the design and implementation of remanufacturing operations in reverse-logistics. Int. J. Prod. Res. 2005, 43:3455-3480.
5. Rubio S., Corominas A. Optimal manufacturing-remanufacturing policies in a lean production environment. Comput. Ind. Eng. 2008, 55:234-242.
6. Mukhopadhyay S.K., Ma H. Joint procurement and production decisions in remanufacturing under quality and demand uncertainty. Int. J. Prod. Econ. 2009, 120:5-17.
7. Konstantaras I., Papachristos S. Optimal policy and holding cost stability regions in a periodic review inventory system with manufacturing and remanufacturing options. Eur. J. Oper. Res. 2007, 178:433-448.
8. Min H., Ko C.S., Ko H.J. The spatial and temporal consolidation of returned products in a closed-loop supply chain network. Comput. Ind. Eng. 2006, 51:309-320.
9. Guide D., Jayaraman V., Linton J. Building contingency planning for closed-loop supply chains with product recovery. J. Oper. Manage. 2003, 21:259-279.
10. Ketzenberg M.E., van der Laan E., Teunter R.H. Value of information in closed loop supply chains. Product. Oper. Manage. 2006, 15:393-406.
11. Shi J., Zhang G., Sha J. Optimal production planning for a multi-product closed loop system with uncertain demand and return. Comput. Oper. Res. 2011, 38:641-650.
12. Xie Y., Petrovic D., Burnham K. A heuristic procedure for the two-level control of serial supply chains under fuzzy customer demand. Int. J. Prod. Econ. 2006, 102:37-50.
13. Handfield R., Warsing D., Wu X. (Q r) inventory policies in a fuzzy uncertain supply chain environment. Eur. J. Oper. Res. 2009, 197:609-619.
14. Zimmermann H. An application-oriented view of modelling uncertainty. Eur. J. Oper. Res. 2000, 122:190-198.
15. Zadeh L. Fuzzy sets. Inf. Control 1965, 8:338-353.
16. Nahmias S. Fuzzy variables. Fuzzy Sets Syst. 1978, 1:97-110.
17. Kaufmann A., Gupta M. Introduction to Fuzzy Arithmetic: Theory and Applications 1985, Van Nostrand Reinhold, New York.
18. Liu B. A survey of credibility theory. Fuzzy Optim. Decis. Mak. 2006, 5:387-408.
19. Liu B., Liu Y. Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst. 2002, 10:445-450.
20. Wang J., Shu Y. Fuzzy decision modeling for supply chain management. Fuzzy Sets Syst. 2005, 150:107-127.
21. Petrovic D., Roy R., Petrovic R. Supply chain modeling using fuzzy sets. Int. J. Prod. Econ. 1999, 59:443-453.
22. Chou S.Y., Peterson Julian C., Hung K.C. A note on fuzzy inventory model with storage space and budget constraints. Appl. Math. Model. 2009, 33:4069-4077.
23. Mondal S., Maiti M. Multi-item fuzzy EOQ models using genetic algorithm. Comput. Ind. Eng. 2002, 44:105-117.
24. Zhao J., Tang W., Zhao R., Wei J. Pricing decisions for substitutable products with a common retailer in fuzzy environments. Eur. J. Oper. Res. 2012, 216:409-419.
25. Giannaoccaro I., Pontrandolfo P., Scozzi B. A fuzzy echelon approach for inventory management. Eur. J. Oper. Res. 2003, 149:185-196.
26. Wei J., Zhao J. Pricing decisions with retail competition in a fuzzy closed-loop supply chain. Expert Syst. Appl. 2011, 38:11209-11216.
27. Xu R., Zhai X. Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain. Appl. Math. Model. 2010, 34:129-139.
28. S. Ebrahimnejad, S.M. Mousavi, R. Tavakkoli-Moghaddam, H. Hashemi, B. Vahdani, A novel two-phase group decision making approach for construction project selection in a fuzzy environment, Appl. Math. Model. http://dx.doi.org/10.1016/j.apm.2011.11.050.
29. Liu B., Theory, Programming Practice of Uncertain Physica-Verlag 2002, Heidelberg.
30. Zadeh L. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1978, 1:3-28.
31. Liu B. Uncertain Theory: An Introduction to Its Axiomatic Foundations 2004, Springer, Verlag, Berlin.
32. Wang C., Tang W., Zhao R. On the continuity and convexity analysis of the expected value function of a fuzzy mapping. J. Uncertain Syst. 2007, 1:148-160.
33. Liu Y., Liu B. Expected value operator of random fuzzy variable and random fuzzy expected value models. Int. J. Uncertain Fuzz. Knowl. Based Syst. 2003, 11:195-215.