A series system with returns: Stationary analysis

Operations Research

Volumn 53, Issue 2, 2005, Pages 350-362

  DeCroix, Gregory ^a   Song, Jing Sheng ^a   Zipkin, Paul ^a  

^a DUKE UNIVERSITY   (United States)

Author keywords

Environment: product recovery and remanufacturing; Inventory production: multiechelon

Indexed keywords

ALGORITHMS; INVENTORY CONTROL; PRODUCTION CONTROL; PUBLIC POLICY; RANDOM PROCESSES;

ENVIRONMENT; INVENTORY/PRODUCTION; MULTIECHLEON; PRODUCT RECOVERY AND MANUFACTURING;

OPERATIONS RESEARCH;

EID: 18744376307     PISSN: 0030364X     EISSN: None     Source Type: Journal    
DOI: 10.1287/opre.1040.0184     Document Type: Article

References (27)

1. Chen, F., Y. Zheng. 1994. Lower bounds for multi-echelon stochastic inventory systems. Management Sci. 40 1426-1443.
2. Clark, A., H. Scarf. 1960. Optimal policies for a multi-echelon inventory problem. Management Sci. 6 475-490.
3. Cohen, M., S. Nahmias, W. Pierskalla. 1980. A dynamic inventory system with recycling. Naval Res. Logist. Quart. 27 289-296.
4. DeCroix, G. 2005. Optimal inventory policy for a multi-echelon inventory system with remanufacturing. Oper. Res. Forthcoming.
5. Diem, W. 1999. Makers must dispose of autos. Detroit Free Press (September 2) 4.
6. Federgruen, A., P. Zipkin. 1984. Computational issues in an infinite-horizon, multiechelon inventory model. Oper. Res. 32 818-836.
7. Fleischmann, M. 2000. Quantitative models for reverse logistics. Ph.D. thesis, Erasmus University, Rotterdam, The Netherlands.
8. Fleischmann, M., R. Kuik, R. Dekker. 2002. Controlling inventories with stochastic item returns: A basic model. Eur. J. Oper. Res. 138 63-75.
9. Fleischmann, M., J. Bloemhof-Ruwaard, R. Dekker, E. van der Laan, J. van Nunen, L. van Wassenhove. 1997. Quantitative models for reverse logistics: A review. Eur. J. Oper. Res. 103 1-17.
10. Frankel, C. 1996. The environment. IEEE Spectrum 33(1) 76-81.
11. Hariharan, R., P. Zipkin. 1995. Customer-order information, leadtimes, and inventories. Management Sci. 41 1599-1607.
12. Heyman, D., M. Sobel. 1984, Stochastic Models in Operations Research, Vol. II. McGraw-Hill, New York.
13. Inderfurth, K. 1997. Simple optimal replenishment and disposal policies for a product recovery system with leadtimes. OR Spektrum 19 111-122.
14. Kelle, P., E. Silver. 1989. Purchasing policy of new containers considering the random returns of previously issued containers. IIE Trans. 21 349-354.
15. Kiesmüller, G., E. van der Laan. 2001. An inventory model with dependent product demands and returns. Internat. J. Production Econom. 72 73-87.
16. Mahadevan, B., D. Pyke, M. Fleischmann. 2003. Periodic review, push inventory policies for remanufacturing. Eur. J. Oper. Res. 151 536-551.
17. Parker, R., R. Kapuscinski. 2004. Optimal policies for a capacitated twoechelon inventory system. Oper. Res. 52 739-755.
18. Scarf, H. 1960. The optimality of (s, S) policies in the dynamic inventory problem. K. Arrow, S. Karlin, P. Suppes, eds. Mathematical Models in the Social Sciences. Stanford University Press, Stanford, CA.
19. Schenkman, L. 2002. EU government to enforce e-waste recycling. Waste Age 33 14.
20. Shang, K., J. Song. 2003. Newsvendor bounds and heuristic for optimal policies in serial supply chains. Management Sci. 49 618-638.
21. Simpson, V. 1978. Optimum solution structure for a repairable inventory problem. Oper. Res. 26 270-281.
22. Song, J. 1994. The effect of leadtime uncertainty in a simple stochastic inventory model. Management Sci. 40 603-613.
23. Tedeschi, B. 2001. Online retailers grapple with the age-old problem of handling returned merchandise. The New York Times (May 28) C6.
24. Thorn, B., P. Rogerson. 2002. Take it back. IIE Solutions 34 34-40.
25. Veinott, A. 1965. Optimal policy for a multi-product, dynamic, nonstationary inventory problem. Management Sci. 12 206-222.
26. Wolff, R. 1989. Stochastic Models and the Theory of Queues. Prentice-Hall, Englewood Cliffs, NJ.
27. Zipkin, P. 2000. Foundations of Inventory Management. McGraw-Hill, New York.