Approximate solutions of a dynamic forecast-inventory model

Manufacturing and Service Operations Management

Volumn 8, Issue 4, 2006, Pages 407-425

  Iida, Tetsuo ^a   Zipkin, Paul H ^b  

^a KOMAZAWA UNIVERSITY   (Japan)

^b DUKE UNIVERSITY   (United States)

Author keywords

Approximate solutions; Demand forecasts; Inventory

Indexed keywords

APPROXIMATE SOLUTIONS; DEMAND FORECASTS; FUNCTION APPROXIMATION;

APPROXIMATION THEORY; COMPUTER SIMULATION; FUNCTION EVALUATION; MATHEMATICAL MODELS; OPTIMAL CONTROL SYSTEMS; STATE SPACE METHODS;

TECHNOLOGICAL FORECASTING;

EID: 33749365674     PISSN: 15234614     EISSN: 15265498     Source Type: Journal    
DOI: 10.1287/msom.1060.0116     Document Type: Article

References (29)

1. Bertsekas, D., J. Tsitsiklis. 1996. Neuro-Dynamic Programming. Athena Scientific, Belmont, MA.
2. Chen, V., D. Ruppert, C. Shoemaker. 1999. Applying experimental design and regression splines to high-dimensional continuous-state stochastic dynamic programming. Oper. Res. 47 38-53.
3. de Frias, D., B. Van Roy. 2003. The linear programming approach to approximate dynamic programming. Oper. Res. 51 850-865.
4. Dong, L., H. Lee. 2003. Optimal policies and approximations for a serial multi-echelon inventory system with time-correlated demand. Oper. Res. 51 969-980.
5. Erkip, N., W. Hausman, S. Nahmias. 1990. Optimal centralized ordering policies in multi-echelon inventory systems with correlated demands. Management Sc. 36 381-392.
6. Gallego, G., Ö. Özer. 2001. Integrating replenishment decisions with advance demand information. Management Sc. 47 1344-1360.
7. Graves, S. 1999. A single-item inventory model for a nonstationary demand process. Manufacturing Senrice Oper. Management 1 50-61.
8. Graves, S., D. Kletter, W. Hetzel. 1998. A dynamic model for requirements planning with application to supply chain optimization. Oper. Res. 46 S35-S49.
9. Graves, S., H. Meal, S. Dasu, Y. Qin. 1986. Two-stage production planning in a dynamic environment. S. Axsäter, C. Schneeweiss, E. Silver, eds. Multi-Stage Production Planning and Control. Lecture Notes in Economics and Mathematical Systems. Springer-Verlag, Berlin, Germany, 9-43.
10. Güllü, R. 1996. On the value of information in dynamic production/inventory problems under forecast evolution. Naval Res. Logist. 43 289-303.
11. Hausman, W. H. 1969. Sequential decision problems: A model to exploit existing forecasters. Management Sci. 16 B93-B111.
12. Heath, D., P. Jackson. 1994. Modeling the evolution of demand forecasts with application to safety stock analysis in prodution/distribution sytems. IIE Trans. 26 17-30.
13. Iida, T. 1999. The infinite horizon non-stationary stochastic inventory problem: Near myopic policies and weak ergodicity. Eur. J. Oper. Res. 116 405-422.
14. Johnson, G., H. Thompson. 1975. Optimality of myopic inventory policies for certain dependent demand process. Management Sci. 21 1303-1307.
15. Johnson, S., J. Stedinger, C. Shoemaker, Y. Li, J. Tejada-Guibert. 1993. Numerical solution of continuous-state dynamic programs using linear and spline interpolation. Oper. Res. 41 484-500.
16. Karlin, S. 1960a. Dynamic inventory policy with varying stochastic demands. Management Sci. 6 231-258.
17. Karlin, S. 1960b. Optimal policy for dynamic inventory process with stochastic demands subject to seasonal variations. J. SIAM 8 611-629.
18. Lovejoy, W. 1992. Stopped myopic policies for some inventory models with uncertain demand distributions. Management Sci. 38 688-707.
19. Miller, B. 1986. Scarf's state reduction method, flexibility, and a dependent demand inventory model. Oper. Res. 34 83-90.
20. Morton, T. 1978. The nonstationary infinite horizon inventory problem. Management Sci. 24 1474-1482.
21. Morton, T., D. Pentico. 1995. The finite horizon nonstationary stochastic inventory problem: Near-myopic bounds, heuristics, testing. Management Sci. 41 334-343.
22. Reyman, G. 1989. State reduction in a dependent demand inventory model given by a time series. Eur. J. Oper. Res. 41 174-180.
23. Schäl, M. 1976. On the optimality of (s, S)-policies in dynamic inventory models with finite horizon. SIAM J. Appl. Math. 30 528-537.
24. Song, J., P. Zipkin. 1993. Inventory control in a fluctuating demand environment. Oper. Res. 41 351-370.
25. Toktay, L., L. Wein. 1999. Analysis of a forecasting-production-inventory system with stationary demand. Management Sci. 47 1268-1281.
26. Veinott, A. 1963. Optimal stockage policies with non-stationary stochastic demands. H. Scarf, D. Gilford, M. Shelly, eds. Multi-stage Inventory Models and Techniques. Stanford University Press, Stanford, CA, 85-115.
27. Veinott, A. 1965. Optimal policy for a multi-product, dynamic, nonstationary inventory problem. Management Sci. 12 206-222.
28. Zipkin, P. 1989. Critical number policies for inventory models with periodic data. Management Sci. 35 71-80.
29. Zipkin, P. 2000. Foundations of Inventory Management. McGraw-Hill, New York.