Capacitated Multi-Item Inventory Systems with Random and Seasonally Fluctuating Demands: Implications for Postponement Strategies

References

  • Aviv Y. Planning models for the design of capacitated multistage production and distribution systems. (1998) (Columbia University, New York) . Ph.D. dissertation,UMI #9838877Google Scholar
  • Aviv Y., Federgruen A. Stochastic inventory models with limited production capacity and periodically varying parameters. Prob. Engrg. Inform. Sci. (1997a) 11:107–135CrossrefGoogle Scholar
  • Aviv Y., Federgruen A. Designfor postponement: A comprehensive characterization of its benefits under unknown demand distributions. Oper. Res. (1997b) . ForthcomingGoogle Scholar
  • Aviv Y., Federgruen A., Tayur S., Magazine M., Ganeshan R. The benefits of design for postponement. Quantitative Modeling for Supply Chain Management (1998) (Kluwer Academic Publishers)Google Scholar
  • Aviv Y., Federgruen A.Technical addendum to: Capacitated multi-item inventory systems with random and seasonally fluctuating demands: Implications for postponement strategies (1999) (Washington University, St. Louis, MO, and Columbia University, New York, NY) Google Scholar
  • Beyer D., Sethi S. P. Average cost optimality in inventory models with Markovian demands. J. Optim. Theor. Appl. (1997) 92(3):497–526CrossrefGoogle Scholar
  • Cheng F., Sethi S. P.Optimality of state-dependent (s, S) policies in Markovian demand inventory models withlost sales (1995) (Faculty of Management, University of Toronto, Ontario, Canada) . Working paperGoogle Scholar
  • Cheng F., Zheng Y. S. Lower bounds for multi-echelon stochastic inventory systems. Management Sci. (1994) 40:1426–1443LinkGoogle Scholar
  • Ciarallo F. W., Akella R., Morton T. E. A periodic review, production planning model with uncertain capacity and uncertain demand—optimality of extended myopic policies. Management Sci. (1994) 40:320–332LinkGoogle Scholar
  • Clark A. J., Scarf H. Optimal policies for a multi-echelon inventory problem. Management Sci. (1960) 6:475–490LinkGoogle Scholar
  • Eppen G., Schrage L., Schwarz L. Centralized ordering policies in a multiwarehouse system with leadtimes and random demands. Multi-Level Production/Inventory Control Systems: Theory and Practice (1981) (North-Holland, Amsterdam, The Netherlands) 51–69Google Scholar
  • Evans R. Inventory control of a multiproduct system with a limited production resource. Naval Res. Logist. Quart. (1967) 14:173–184CrossrefGoogle Scholar
  • Federgruen A., Graves S., Rinnooy Kan A., Zipkin P. Centralized planning models for multi-echelon inventory systems under uncertainty. Handbook in Operations Research and Management Science (1992) (North-Holland, Amsterdam, The Netherlands) Google Scholar
  • Federgruen A., Sarin R. Recent advances in production and distribution management. Perspectives in Operations Management (1993) (Kluwer Academic Publishers, Norwell, MA) CrossrefGoogle Scholar
  • Federgruen A.Comments on: Variability reduction through operations reversal in supply chain re-engineering (1999) (Columbia University, New York) . Working paperGoogle Scholar
  • Federgruen A., Zipkin P. Approximations of dynamic, multilocation production and inventory problems. Management Sci. (1984a) 30:69–84LinkGoogle Scholar
  • Federgruen A., Zipkin P. Allocation policies and cost approximations for multilocation inventory systems. Naval Res. Logist. Quart. (1984b) 31:97–129CrossrefGoogle Scholar
  • Federgruen A., Zipkin P. Computational issues in an infinite horizon multi-echelon inventory model. Oper. Res. (1984c) 32:818–832LinkGoogle Scholar
  • Fisher M. L., Raman A. Reducing the cost of demand uncertainty through accurate response to early sales. Oper. Res. (1996) 44:87–99LinkGoogle Scholar
  • Flaherty M. T.Global Operations Management (1996) (McGraw-Hill)Google Scholar
  • Flaherty M. T., Cohen M., Kopczak L., Lee H., Pyke D.Teaching note for Hewlett Packard: DeskJet printer supply chain (A) (1996) (The Wharton School, University of Pennsylvania, Philadelphia, PA) Google Scholar
  • Fox B. Discrete optimization via marginal analysis. ManagementSci. (1966) 4:36–153Google Scholar
  • Gallego G., Zipkin P.Bounds, heuristics and approximations for distribution systems (1997) (Columbia University, Duke University, New York, NY, Durham, NC) . Working paperGoogle Scholar
  • Garg A., Lee H. L., Tayur S., Magazine M., Ganeshan R. Managing productvariety: An operations perspective. Quantitative Modeling for Supply Chain Management (1998) (Kluwer Academic Publishers)Google Scholar
  • Gonsalvez D.Integrating sales and manufacturing order management processes applied scheduling: Integration of disciplines (1991) (Columbia University, New York) . Working paperGoogle Scholar
  • Gross O.A class of discrete-type minimization problems (1956) (The RAND Corporation, Santa Monica, CA) . Working paper RM-1644-PRGoogle Scholar
  • Kapuscinski R., Tayur S. A capacitated production-inventory model with periodic demand. Oper. Res. (1998) 46(6):899–911LinkGoogle Scholar
  • Kapuscinski R., Tayur S. Variance vs. standard deviation—variability reduction through operations reversal. Management Sci. (1999) 45:765–767LinkGoogle Scholar
  • Kopczak L., Lee H.Hewlett Packard: DeskJet printer supply chain (A) (1993) (Case study, Stanford University, Stanford, CA) Google Scholar
  • Lee H., Sarin R. Design for supply chain management: Concepts and examples. Perspectives in Operations Management (1993) (Kluwer Academic Publishers, Norwell, MA) CrossrefGoogle Scholar
  • Lee H. L., Billington C. The evolution of supply chain models and practice at Hewlett-Packard. Interfaces (1995) 25(5):42–63LinkGoogle Scholar
  • Lee H. L., Billington C., Carter B. Hewlett-Packard gains control of inventory and service through design for localization. Interfaces (1993) 23(4):1–11LinkGoogle Scholar
  • Lee H. L., Tang C. S. Modeling the costs and benefits of delayed product differentiation. Management Sci. (1997) 43LinkGoogle Scholar
  • Lee H. L., Tang C. S. Variability reduction through operations reversal. Management Sci. (1998) 44:162–173LinkGoogle Scholar
  • Metters R. Producing multiple products with stochastic seasonal demand and capacity limits. J. Oper. Res. Soc. (1998) 49:263–272CrossrefGoogle Scholar
  • Signorelli S., Heskett J. L.Benetton (A) (1989) (Harvard Business School, Boston, MA) . Working paperGoogle Scholar
  • Song J. S., Zipkin P. Inventory control in a fluctuating demand environment. Oper. Res. (1993) 41:351–370LinkGoogle Scholar
  • Zipkin P. Exact and approximate cost functions for product aggregates. Management Sci. (1982) 28:1002–1012LinkGoogle Scholar
  • Zipkin P. Critical number policies for inventory model with periodic data. Management Sci. (1989) 35:71–80LinkGoogle Scholar
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